American Community Survey

Description

Data from a sample of individuals in the American Community Survey

Format

A data frame with 10,000 observations on the following 9 variables.

Sex

0=female and 1=male

Age

Age (years)

Married

0=not married and 1=married

Income

Wages and salary for the past 12 months (in $1,000's)

HoursWk

Hours of work per week

Race

Asian, Black, Other, or White

USCitizen

1=citizen and 0=noncitizen

HealthInsurance

1=have health insurance and 0=no health insurance

Language

1=English spoken at home and 0=other

Details

The American Community Survey, administered by the US Census Bureau, is given every year to a random sample of about 3.5 million households (about 3% of all US households). Data on a random sample of 1% of all US residents are made public (after ensuring anonymity), and we have selected a random sub-sample of n = 10000 from the 2023 data for this dataset.
** Updated for 4e (earlier versions are ACS3e (from 2017) and ACS2010). **

Source

The full public dataset can be downloaded at https://www.census.gov/programs-surveys/acs/microdata.html, and the full list of variables are at https://www.census.gov/programs-surveys/acs/microdata/documentation.html

Specific request for these variables is https://data.census.gov/app/mdat/ACSPUMS1Y2023/table?cv=SEX,MAR,RAC1P,HICOV&vv=AGEP,WAGP,WKHP&rv=CIT,LANX&wt=PWGTP

American Community Survey - 2010

Description

Data from a sample of individuals in the 2010 American Community Survey

Format

A dataset with 1000 observations on the following 9 variables.

Details

The American Community Survey, administered by the US Census Bureau, is given every year to a random sample of about 3.5 million households (about 3% of all US households). Data on a random sample of 1% of all US residents are made public (after ensuring anonymity), and we have selected a random sub-sample of n = 1000 from the 2010 data for this dataset.

** From 2e - dataset has been updated for 3e **

Source

The full public dataset can be downloaded at
http://www.census.gov/acs/www/data documentation/pums data/,
and the full list of variables are at
http://www.census.gov/acs/www/Downloads/data documentation/pums/DataDict/PUMSDataDict10.pdf.

American Community Survey - 3e

Description

Data from a sample of individuals in the American Community Survey

Format

A data frame with 2000 observations on the following 9 variables.

Sex

0=female and 1=male

Age

Age (years)

Married

0=not married and 1=married

Income

Wages and salary for the past 12 months (in $1,000's)

HoursWk

Hours of work per week

Race

asian, black, other, or white

USCitizen

1=citizen and 0=noncitizen

HealthInsurance

1=have health insurance and 0=no health insurance

Language

1=English spoken at home and 0=other

Details

The American Community Survey, administered by the US Census Bureau, is given every year to a random sample of about 3.5 million households (about 3% of all US households). Data on a random sample of 1% of all US residents are made public (after ensuring anonymity), and we have selected a random sub-sample of n = 2000 from the 2017 data for this dataset.
** Updated for 3e (earlier version is ACS2010). **

Source

The full public dataset can be downloaded at https://www.census.gov/programs-surveys/acs/microdata.html, and the full list of variables are at https://www.census.gov/programs-surveys/acs/microdata/documentation.html

AP Multiple Choice

Description

Correct responses on Advanced Placement multiple choice exams

Format

A dataset with 400 observations on the following variable.

Details

Correct responses from multiple choice sections for a sample of released Advanced Placement exams

Source

Sample exams from several disciplines at http://apcentral.collegeboard.com

All Countries

Description

Data on the countries of the world

Format

A data frame with 217 observations on the following 29 variables.

Country

Country name

Code

Three-letter code for country

LandArea

Size in 1000 sq. km.

Population

Population in millions

Density

Number of people per square kilometer

GDP

Gross Domestic Product (in $US) per capita

Rural

Percentage of population living in rural areas

CO2

CO2 emissions (metric tons per capita)

PumpPrice

Price for a liter of gasoline ($US)

Military

Percentage of government expenditures directed toward the military

Health

Percentage of government expenditures directed towards healthcare

ArmedForces

Number of active duty military personnel (in 1,000's)

Internet

Percentage of the population with access to the internet

Cell

Cell phone subscriptions (per 100 people)

HIV

Percentage of the population with HIV

Hunger

Percent of the population considered undernourished

Diabetes

Percent of the population diagnosed with diabetes

BirthRate

Births per 1000 people

DeathRate

Deaths per 1000 people

ElderlyPop

Percentage of the population at least 65 years old

LifeExpectancy

Average life expectancy (years)

FemaleLabor

Percent of females 15 - 64 in the labor force

Unemployment

Percent of labor force unemployed

Renewable

Percent of energy from renewable sources

Energy

Total energy consumption (million BTU per capita)

Electricity

Electric power consumption (kWh per capita)

Developed

Categories for kilowatt hours per capita, 1= under 2500, 2=2500 to 5000, 3=over 5000

HDI

Human Development Index - United Nations' measure of social and economic well being on a 0-1 scale

HDIGroup

Categories (Very High, High, Medium, Low) based on HDI

Details

Most data for each variable were collected for 2023 (or most recently available year) from https://data.worldbank.org/. Energy and Electricity values come from U.S. Energy Information Administration. HDI values from United Nations Human Development Report.

** This dataset is updated for 4e from earlier versions (now Allcountries1e, AllCountries2e, and All Countries3e) **

Source

Most data were gathered online from https://data.worldbank.org/.

Gasoline prices come from https://tradingeconomics.com/country-list/gasoline-prices?continent=world.

Electicity and Energy variables from U.S. Energy Information Administration, https://www.eia.gov/international/data/world#/

HDI variables from United Nations Human Development Report, https://hdr.undp.org/data-center/human-development-index#/indicies/HDI All accessed January 2025.

AllCountries - 1e

Description

Data on the countries of the world (1e)

Format

A dataset with 213 observations on the following 18 variables.

Details

Most data from 2008 to avoid many missing values in more recent years.
** From 1e - dataset has been updated for 2e **

Source

Data collected from the World Bank website, worldbank.org.

AllCountries - 2e

Description

Data on the countries of the world (2e)

Format

A dataset with 215 observations on the following 25 variables.

Details

Data for each variable were collected for years between 2012 and 2014. Within a variable all country measurements are from the same year, but the year may vary between different variables depending on availability.
** From 2e - dataset has been updated for 3e **

Source

Data collected from the World Bank website, worldbank.org.

All Countries-3e

Description

Data on the countries of the world (3e)

Format

A data frame with 217 observations on the following 26 variables.

Country

Country name

Code

Three-letter code for country

LandArea

Size in 1000 sq. km.

Population

Population in millions

Density

Number of people per square kilometer

GDP

Gross Domestic Product (in $US) per capita

Rural

Percentage of population living in rural areas

CO2

CO2 emissions (metric tons per capita)

PumpPrice

Price for a liter of gasoline ($US)

Military

Percentage of government expenditures directed toward the military

Health

Percentage of government expenditures directed towards healthcare

ArmedForces

Number of active duty military personnel (in 1,000's)

Internet

Percentage of the population with access to the internet

Cell

Cell phone subscriptions (per 100 people)

HIV

Percentage of the population with HIV

Hunger

Percent of the population considered undernourished

Diabetes

Percent of the population diagnosed with diabetes

BirthRate

Births per 1000 people

DeathRate

Deaths per 1000 people

ElderlyPop

Percentage of the population at least 65 years old

LifeExpectancy

Average life expectancy (years)

FemaleLabor

Percent of females 15 - 64 in the labor force

Unemployment

Percent of labor force unemployed

Energy

Kilotons of oil equivalent

Electricity

Electric power consumption (kWh per capita)

Developed

Categories for kilowatt hours per capita, 1= under 2500, 2=2500 to 5000, 3=over 5000

Details

Data for each variable were collected for 2018 (or most recently available year). Within a variable all country measurements are from the same year, but the year may vary between different variables depending on availability.
** This dataset is updated from an earlier versions (now Allcountries1e and AllCountries2e) **

Source

The data were gathered online from https://data.worldbank.org/. Accessed June 2019.

April 14th Temperatures

Description

Temperatures in Des Moines, IA and San Francisco, CA on April 14th

Format

A data frame with 30 observations on the following 3 variables.

Year

1995 to 2024

DesMoines

Temperature in Des Moines (degrees F)

SanFrancisco

Temperature in San Francisco (degrees F)

Details

Average temperature for the day of April 14th in each of 30 years from 1995-2024
** Data set updated for 4e (earlier versions are now April14Temps3e, April14Temps2e, and April14Temps1e) **

Source

Original data downaded from the University of Dayton Average Daily Temperature Archive at https://academic.udayton.edu/kissock/http/Weather/citylistUS.htm

Recent updates from https://www.wunderground.com/history/daily/us/ca/san-francisco/KSFO and https://www.wunderground.com/history/daily/us/ia/des-moines/KDSM

April 14th Temperatures -1e

Description

Temperatures in Des Moines, IA and San Francisco, CA on April 14th

Format

A dataset with 16 observations on the following 3 variables.

Details

Average temperature for the day of April 14th in each of 16 years from 1995-2010
** From 1e - dataset has been updated for 2e **

Source

The University of Dayton Average Daily Temperature Archive downloaded from
http://academic.udayton.edu/kissock/http/Weather/citylistUS.htm

April 14th Temperatures - 2e

Description

Temperatures in Des Moines, IA and San Francisco, CA on April 14th

Format

A dataset with 21 observations on the following 3 variables.

Details

Average temperature for the day of April 14th in each of 21 years from 1995-2015
** From 2e - dataset has been updated for 3e **

Source

The University of Dayton Average Daily Temperature Archive at
http://academic.udayton.edu/kissock/http/Weather/citylistUS.htm

April 14th Temperatures - 3e

Description

Temperatures in Des Moines, IA and San Francisco, CA on April 14th

Format

A data frame with 25 observations on the following 3 variables.

Year

1995 to 2019

DesMoines

Temperature in Des Moines (degrees F)

SanFrancisco

Temperature in San Francisco (degrees F)

Details

Average temperature for the day of April 14th in each of 25 years from 1995-2019
** Data set updated for 3e (earlier versions are now April14Temps1e and April14Temps2e) **

Source

Original data downaded from the University of Dayton Average Daily Temperature Archive at https://academic.udayton.edu/kissock/http/Weather/citylistUS.htm

Recent updates from https://www.wunderground.com/history/daily/us/ca/san-francisco/KSFO and https://www.wunderground.com/history/daily/us/ia/des-moines/KDSM

Body Mass Index and Exercise

Description

Body Mass Index (BMI) and exercsie indicator from the 2023 BRFSS survey

Format

A data frame with 392,788 observations on the following 2 variables.

BMI

Body Mass Index = weight (in kg) / (height (in m))^2

Exercise

Have you exercised in last 30 days? (Yes or No)

Details

Data from the 2023 Behavioral Risk Factor Surveillance System (BRFSS) survey. BMI is calculated as weight (in kg) divided by height (in meters) squared. Values above 25 are considered overweight and over 30 are clasified as obese.

Source

Centers for Disease Control and Prevention (CDC), Behavioral Risk Factor Surveillance System Survey Data, U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, Atlanta, 2023. https://www.cdc.gov/brfss/annual_data/annual_2023.html

Baseball Hits

Description

Number of hits, wins, and other stats for MLB teams - 2011

Format

A dataset with 30 observations on the following 14 variables.

Details

Data from the 2010 Major League Baseball regular season.
** From 1e - dataset has been updated for 2e **

Source

http://www.baseball-reference.com/leagues/MLB/2011-standard-batting.shtml

Baseball Hits - 2014

Description

Number of hits, wins, and other stats for MLB teams - 2014

Format

A dataset with 30 observations on the following 14 variables.

Details

Data from the 2014 Major League Baseball regular season.
** From 2e - dataset has been updated for 3e **

Source

http://www.baseball-reference.com/leagues/MLB/2014-standard-batting.shtml

Baseball Team Statistics (2019)

Description

Number of hits, wins, and other stats for MLB teams in 2019

Format

A data frame with 30 observations on the following 14 variables.

Team

Name of baseball team (3-character code)

League

Either AL or NL

Wins

Number of wins for the season

Runs

Number of runs scored

Hits

Number of hits

Doubles

Number of doubles

Triples

Number of triples

HomeRuns

Number of home runs

RBI

Number of runs batted in

StolenBases

Number of stolen bases

CaughtStealing

Number of times caught stealing

Walks

Number of walks

Strikeouts

Number of strikeouts

BattingAvg

Team batting average

Details

Offensive team statistics for the 2019 Major League Baseball regular season.
** Updated for 3e (earlier versions are now BaseballHits2014, and BaseballHits1e)

Source

https://www.baseball-reference.com/leagues/MLB/2019-standard-batting.shtml

Baseball Team Statistics (2024)

Description

Number of hits, wins, and other stats for MLB teams in 2024

Format

A data frame with 30 observations on the following 14 variables.

Team

Name of baseball team (3-character code)

League

Either AL or NL

Wins

Number of wins for the season

Runs

Number of runs scored

Hits

Number of hits

Doubles

Number of doubles

Triples

Number of triples

HomeRuns

Number of home runs

RBI

Number of runs batted in

StolenBases

Number of stolen bases

CaughtStealing

Number of times caught stealing

Walks

Number of walks

Strikeouts

Number of strikeouts

BattingAvg

Team batting average

Details

Offensive team statistics for the 2024 Major League Baseball regular season.
** Updated for 4e (earlier versions are now BaseballHits2019, BaseballHits2014, and BaseballHits1e)

Source

https://www.baseball-reference.com/leagues/MLB/2024-standard-batting.shtml

MLB Player Salaries in 2015

Description

Opening Day salaries for all Major League Baseball players in 2015

Format

A dataset with 868 observations on the following 4 variables.

Details

Yearly salary (in millions of dollars) for all players on the rosters of Major League Baseball teams at the start of the 2015 season.
** From 2e - dataset has been updated for 3e **

Source

http://www.usatoday.com/sports/mlb/salaries

MLB Player Salaries in 2019

Description

Opening Day salaries for all Major League Baseball players in 2019

Format

A data frame with 877 observations on the following 4 variables.

Name

Player's name

Salary

2019 season salary (in millions)

Team

Abbreviated team name

POS

Code for player's main position

Details

Yearly salary (in millions of dollars) for all players on the rosters of Major League Baseball teams at the start of the 2019 season.
** Updated for 3e (earlier version for 2015 is at BaseballSalaries2015). **

Source

https://databases.usatoday.com/mlb-salaries/

MLB Player Salaries in 2024

Description

Opening Day salaries for all Major League Baseball players in 2024

Format

A data frame with 952 observations on the following 4 variables.

Name

Player's name

Salary

2024 season salary (in millions)

Team

Team name

Pos

Code for player's main position

Details

Yearly salary (in millions of dollars) for all players on the rosters of Major League Baseball teams at the start of the 2024 season.
** Updated for 4e (earlier versions are BaseballSalaries2019 and BaseballSalaries2015). **

Source

Downloaded from USA Today at https://databases.usatoday.com/major-league-baseball-salaries-2024/. (March 2025)

Baseball Game Times (2024)

Description

Information for a sample of 50 Major League Baseball games played during the 2024 season

Format

A dataset with 50 observations on the following 9 variables.

Details

Data from a sample of boxscores for Major League Baseball games played during the 2024 season. Games include all played on May 6th, June 6th, July 13th, and August 16th,

Source

Data obtained from boxscores at https://www.baseball-reference.com/boxes/index.fcgi

Baseball Game Times (2011)

Description

Information for a sample of 30 Major League Baseball games played during the 2011 season

Format

A dataset with 30 observations on the following 9 variables.

Details

Data from a sample of boxscores for Major League Baseball games played in August 2011.

Source

http://www.baseball-reference.com/boxes/2011.shtml

Benford data

Description

Two examples to test Benford's Law

Format

A dataset with 9 observations on the following 4 variables.

Details

Leading digits from 1188 addresses sampled from a phone book and 7273 amounts from invoices sampled at a company.

Source

Thanks to Prof. Richard Cleary for providing the data

Bike Commute

Description

Commute times for two kinds of bicycle

Format

A dataset with 56 observations on the following 9 variables.

Details

Data from a personal experiment to compare commuting time based on a randomized selection between two bicycles made of different materials.

Source

Thanks to Dr. Groves for providing his data.

References

Bicycle weight and commuting time: randomised trial, in British Medical Journal, BMJ 2010;341:c6801.

Body Measurements

Description

Percent fat and other body measurements for a sample of men

Format

A dataset with 100 observations on the following 10 variables.

Details

This is a subset of a larger sample of men who each had a percent body fat estimated by an underwater weighing technique. Other measurements were taken to see how they might be used to predict the body fat percentage.

Source

These data were contributed by Roger Johnson, then at Carleton University, to the Datasets Archive at the Journal of Statistics Education.
https://ww2.amstat.org/publications/jse/v4n1/datasets.johnson.html
The data were originally supplied by Dr. A. Garth Fisher, Human Performance Research Center, Brigham Young University, Provo, Utah 84602.

Body Temperatures

Description

Sample of 50 body temperatures

Format

A data frame with 50 observations on the following 3 variables.

BodyTemp

Body temperature in degrees F

Pulse

Pulse rates (beat per minute)

Sex

F=Female, M=Male

Details

Body temperatures and pulse rates for a sample of 50 healthy adults. Note the Sex variable was labeled as Gender in earlier versions of this dataset. We acknowledge that this binary dichotomization is not a complete or inclusive representation of reality.

Source

Shoemaker, "What's Normal: Temperature, Gender and Heartrate", Journal of Statistics Education, Vol. 4, No. 2 (1996)
https://jse.amstat.org/v4n2/datasets.shoemaker.html

Bootstrap Correlations for Atlanta Commutes

Description

Bootstrap correlations between Time and Distance for 500 commuters in Atlanta

Format

A dataset with 1000 observations on the following variable.

Details

Correlations for bootstrap samples of Time vs. Distance for the data on Atlanta commuters in CommuteAtlanta.

Source

Computer simulation

CAOS Exam Scores

Description

Scores on a pre-test and post-test of basic statistics concepts

Format

A dataset with 10 observations on the following 3 variables.

Details

The CAOS (Comprehensive Assessment of Outcomes in First Statistics Course) exam is designed to measure comprehension of basic statistical ideas in an introductory statistics course. This dataset has scores for ten students who took the CAOS pre-test at the start of a course and the post-test during the course itself. Each exam consists of 40 multiple choice questions and the score is the percentage correct.

Source

A sample of 10 students from an introductory statistics course. Find out more about the CAOS exam at http://app.gen.umn.edu/artist/caos.html

College Experience Before, During, After Covid

Description

Measures on college students before, during, and after the Covid-19 pandemic

Format

A data frame with 188 observations on the following 28 variables. Values are averages over days in three different period: Before=prior to March 2020, During=March 2020 to July 2021, After = after July 2021.

StillBefore

Time spent still (no movement) in seconds

StepsBefore

Number of steps per day

PhoneUnlockedBefore

Amount of time that a student uses their phone in unlocked state (i.e., total phone usage duration)

SleepBefore

Sleep duration (based on a predictive model) in hours

AnxiousBefore

Over the last 2 weeks, how often have you been bothered by the following problems? Feeling nervous, anxious or on edge (0: Not at all; 1: Several days; 2: More than half the days; 3: Nearly every day)

DepressedBefore

Over the last 2 weeks, how often have you been bothered by the following problems? Feeling down, depressed or hopeless (0: Not at all; 1: Several days; 2: More than half the days; 3: Nearly every day)

SocialBefore

Have you spent most of your time alone or with others today? (1: Almost always alone; 2: Mostly alone, a little time with others; 3: Equal amounts of time alone and with others; 4: Mostly with others, a little time alone; 5: Almost always with others)

FeelGoodBefore

Right now, Overall, I feel good about myself (1: Not at All; 2: A Little Bit; 3: Somewhat; 4: Very Much; 5: Extremely)

StressBefore

Are you feeling stressed now? (1: Not at All; 2: A Little Bit; 3: Somewhat; 4: Very Much; 5: Extremely)

Sex

Self-reported sex of the participant (F, M, or both)

StillDuring

Time spent still (no movement) in seconds

StepsDuring

Number of steps per day

PhoneUnlockedDuring

Amount of time that a student uses their phone in unlocked state (i.e., total phone usage duration)

SleepDuring

Sleep duration (based on a predictive model) in hours

AnxiousDuring

Over the last 2 weeks, how often have you been bothered by the following problems? Feeling nervous, anxious or on edge (0: Not at all; 1: Several days; 2: More than half the days; 3: Nearly every day)

DepressedDuring

Over the last 2 weeks, how often have you been bothered by the following problems? Feeling down, depressed or hopeless (0: Not at all; 1: Several days; 2: More than half the days; 3: Nearly every day)

SocialDuring

Have you spent most of your time alone or with others today? (1: Almost always alone; 2: Mostly alone, a little time with others; 3: Equal amounts of time alone and with others; 4: Mostly with others, a little time alone; 5: Almost always with others)

FeelGoodDuring

Right now, Overall, I feel good about myself (1: Not at All; 2: A Little Bit; 3: Somewhat; 4: Very Much; 5: Extremely)

StressDuring

Are you feeling stressed now? (1: Not at All; 2: A Little Bit; 3: Somewhat; 4: Very Much; 5: Extremely)

StillAfter

Time spent still (no movement) in seconds

StepsAfter

Number of steps per day

PhoneUnlockedAfter

Amount of time that a student uses their phone in unlocked state (i.e., total phone usage duration)

SleepAfter

Sleep duration (based on a predictive model) in hours

AnxiousAfter

Over the last 2 weeks, how often have you been bothered by the following problems? Feeling nervous, anxious or on edge (0: Not at all; 1: Several days; 2: More than half the days; 3: Nearly every day)

DepressedAfter

Over the last 2 weeks, how often have you been bothered by the following problems? Feeling down, depressed or hopeless (0: Not at all; 1: Several days; 2: More than half the days; 3: Nearly every day)

SocialAfter

Have you spent most of your time alone or with others today? (1: Almost always alone; 2: Mostly alone, a little time with others; 3: Equal amounts of time alone and with others; 4: Mostly with others, a little time alone; 5: Almost always with others)

FeelGoodAfter

Right now, Overall, I feel good about myself (1: Not at All; 2: A Little Bit; 3: Somewhat; 4: Very Much; 5: Extremely)

StressAfter

Are you feeling stressed now? (1: Not at All; 2: A Little Bit; 3: Somewhat; 4: Very Much; 5: Extremely)

Details

The COVID-19 pandemic changed college life dramatically for many students. Like many colleges, the college where these data were collected suddenly went remote in March 2020, and for the 2020-2021 school year only about half of the students attended in-person, most classes were held online, and there were strict restrictions on social gatherings. Campus operations returned mostly to normal for the 2021-2022 school year. Students in college from 2018-2022 spanned college life before, during, and after the pandemic-induced changes to college life, and this dataset includes various mobile sensing and mental health variables averaged over these three time periods. \

Note: The dataset CollegeExperience includes many of the same variables on many of the same students, but is limited to data from the 2021-2022 academic year.

Source

Subigya Nepal, et. al. "Capturing the College Experience: A Four-Year Mobile Sensing Study of Mental Health, Resilience, and Behavior of College Students during the Pandemic", Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 8, 1, Article 38 (March 2024).

College Experience Before, During, After Covid (Stacked Format)

Description

Measures on college students before, during, and after the Covid-19 pandemic

Format

A data frame with 492 observations on the following 11 variables. Values are averages over days in each time period.

Period

Before=prior to March 2020, During=March 2020 to July 2021, After = after July 2021

Still

Time spent still (no movement) in seconds

Steps

Number of steps per day

PhoneUnlocked

Amount of time that a student uses their phone in unlocked state (i.e., total phone usage duration)

Sleep

Sleep duration (based on a predictive model) in hours

Anxious

Over the last 2 weeks, how often have you been bothered by the following problems? Feeling nervous, anxious or on edge (0: Not at all; 1: Several days; 2: More than half the days; 3: Nearly every day)

Depressed

Over the last 2 weeks, how often have you been bothered by the following problems? Feeling down, depressed or hopeless (0: Not at all; 1: Several days; 2: More than half the days; 3: Nearly every day)

Social

Have you spent most of your time alone or with others today? (1: Almost always alone; 2: Mostly alone, a little time with others; 3: Equal amounts of time alone and with others; 4: Mostly with others, a little time alone; 5: Almost always with others)

FeelGood

Right now, Overall, I feel good about myself (1: Not at All; 2: A Little Bit; 3: Somewhat; 4: Very Much; 5: Extremely)

Stress

Are you feeling stressed now? (1: Not at All; 2: A Little Bit; 3: Somewhat; 4: Very Much; 5: Extremely)

Sex

Self-reported sex of the participant (F, M, or both)

Details

The COVID-19 pandemic changed college life dramatically for many students. Like many colleges, the college where these data were collected suddenly went remote in March 2020, and for the 2020-2021 school year only about half of the students attended in-person, most classes were held online, and there were strict restrictions on social gatherings. Campus operations returned mostly to normal for the 2021-2022 school year. Students in college from 2018-2022 spanned college life before, during, and after the pandemic-induced changes to college life, and this dataset includes various mobile sensing and mental health variables averaged over these three time periods.

Note: This dataset, COVIDCollegeStacked, contains the same data as COVIDCollege, but rearranged in a different format. Here instead of different variables for each time period, the three time periods are stacked into one variable and an additional variable, Period, denotes whether the data value is from before, during, or after the pandemic-induced changes to college life.)

Source

Subigya Nepal, et. al. "Capturing the College Experience: A Four-Year Mobile Sensing Study of Mental Health, Resilience, and Behavior of College Students during the Pandemic", Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 8, 1, Article 38 (March 2024).

Caffeine Taps

Description

Finger tap rates with and without caffeine

Format

A dataset with 20 observations on the following 2 variables.

Details

Results from a double-blind experiment where a sample of male college students were asked to tap their fingers at a rapid rate. The sample was then divided at random into two groups of ten students each. Each student drank the equivalent of about two cups of coffee, which included about 200 mg of caffeine for the students in one group but was decaffeinated coffee for the second group. After a two hour period, each student was tested to measure finger tapping rate (taps per minute). The goal of the experiment was to determine whether caffeine produces an increase in the average tap rate.

Source

Hand, Daly, Lund, McConway and Ostrowski, Handbook of Small Data Sets, Chapman and Hall, London (1994), pp. 40

Car Depreciation

Description

Depreciation for 20 car models (2024).

Format

A dataset with 20 observations on the following 5 variables.

Details

Twenty car models were selected at random. Original price (in dollars) and value after one year (and 12,000 miles) were recorded for each model. The depreciation is the difference (New-Used). Updated for 4e (earlier version is now CarDepreciation3e)

Source

New and used costs determined using models selected from https://caredge.com/depreciation.

Car Depreciation - 3e

Description

Depreciation for 20 car models in 2015.

Format

A dataset with 20 observations on the following 4 variables.

Details

Twenty car models were selected at random from kellybluebook.com. Original price (in dollars) and value after the car has been driven 10 miles were recorded for each model. The depreciation is the difference (New-Used).

Source

New and used automobile costs determined using 2015 models selected from kellybluebook.com.

Carbon Dioxide Levels

Description

Atmospheric carbon dioxide levels by year

Format

A data frame with 13 observations on the following 2 variables.

Year

Every five years from 1960 to 2020

CO2

Carbon dioxide level in parts per million

Details

Carbon dioxide levels in the atmosphere over a 60 year span from 1960-2020.
** Updated for 4e (earlier versions are now CarbonDioxide3e and CarbonDioxide2e) **

Source

Dr. Pieter Tans, NOAA/ESRL. Values recorded at the Mauna Loa Observatory in Hawaii. https://gml.noaa.gov/ccgg/trends/

Carbon Dioxide Levels - 2e

Description

Atmospheric carbon dioxide levels by year

Format

A dataset with 11 observations on the following 2 variables.

Details

Carbon dioxide levels in the atmosphere over a 50 year span from 1960-2010.
** From 2e - dataset has been updated for 3e **

Source

Dr. Pieter Tans, NOAA/ESRL (www.esrl.noaa.gov/gmd/ccgg/trends/). Values recorded at the Mauna Loa Observatory in Hawaii.

Carbon Dioxide Levels - 3e

Description

Atmospheric carbon dioxide levels by year

Format

A data frame with 12 observations on the following 2 variables.

Year

Every five years from 1960 to 2015

C02

Carbon dioxide level in parts per million

Details

Carbon dioxide levels in the atmosphere over a 55 year span from 1960-2015.
** Updated for 3e (earlier version is now CarbonDioxide2e) **

Source

Dr. Pieter Tans, NOAA/ESRL. Values recorded at the Mauna Loa Observatory in Hawaii. https://gml.noaa.gov/ccgg/trends/

2015 Car Models

Description

Information about new car models in 2015

Format

A dataset with 110 observations on the following 24 variables.

Details

Data for a set of 110 new car models in 2015 based on information in the Consumer Reports.

Source

Data on new car models in 2015 accessed from Consumer Reports website. https://www.consumerreports.org/cars/

2020 Car Models

Description

Information about new car models in 2020

Format

A data frame with 110 observations on the following 21 variables.

Make

Manufacturer (e.g. Chevrolet, Toyota, etc.)

Model

Car model (e.g. Impala, Highlander, ...)

Type

Vehicle category (Hatchback, Minivan, Sedan, Sporty, SUV, or Wagon)

LowPrice

Lowest MSRP (in $1,000)

HighPrice

Highest MSRP (in $1,000)

CityMPG

City miles per gallon (EPA)

HwyMPG

Highway miles per gallon (EPA)

Seating

Seating capacity

Drive

Type of drive (AWD, FWD, or RWD)

Acc030

Time (in seconds) to go from 0 to 30 mph

Acc060

Time (in seconds) to go from 0 to 60 mph

QtrMile

Time (in seconds) to go ¼ mile

Braking

Distance to stop from 60 mph (dry pavement)

FuelCap

Fuel capacity (in gallons)

Length

Length (in inches)

Width

Width (in inches)

Height

Height (in inches)

Wheelbase

Wheelbase (in inches)

UTurn

Diameter (in feet) needed for a U-turn

Weight

Curb weight (in pounds)

Size

Large, Midsized, or Small

Details

Data for a set of 110 new car models in 2020 based on information in the Consumer Reports.
** Updated for 3e (an earlier version from 2015 is at Cars2015). **

Source

Data on new car models in 2020 accessed from Consumer Reports website. https://www.consumerreports.org/cars/

2025 Car Models

Description

Information about new car models in 2025

Format

A data frame with 107 observations on the following 21 variables.

Make

Manufacturer (e.g. Chevrolet, Toyota, etc.)

Model

Car model (e.g. Impala, Highlander, ...)

Type

Vehicle category (Pickup, Hatchback, Minivan, Sedan, Sporty, SUV, or Wagon)

LowPrice

Lowest MSRP (in $1,000)

HighPrice

Highest MSRP (in $1,000)

CityMPG

City miles per gallon (EPA)

HwyMPG

Highway miles per gallon (EPA)

Seating

Seating capacity

Drive

Type of drive (AWD, FWD, or RWD)

Acc030

Time (in seconds) to go from 0 to 30 mph

Acc060

Time (in seconds) to go from 0 to 60 mph

QtrMile

Time (in seconds) to go ¼ mile

Braking

Distance to stop from 60 mph (dry pavement)

FuelCap

Fuel capacity (in gallons)

Length

Length (in inches)

Width

Width (in inches)

Height

Height (in inches)

Wheelbase

Wheelbase (in inches)

UTurn

Diameter (in feet) needed for a U-turn

Weight

Curb weight (in pounds)

Size

Large, Midsized, or Small

Details

Data for a set of 107 new car models in 2025 based on information in Consumer Reports.
** Updated for 4e (an earlier versions sre Cars2020 and Cars2015). **

Source

Data on new car models in 2025 accessed from Consumer Reports website. https://www.consumerreports.org/cars/

2025 EV Car Models

Description

Information about new electic, plug-in hybrid, and hybrid car models in 2025

Format

A data frame with 93 observations on the following 25 variables.

Make

Manufacturer (e.g. Chevrolet, Toyota, etc.)

Model

Car model (e.g. Camry Hybrid, Blazer EV, ...)

Type

Vehicle category (Pickup, Hatchback, Minivan, Sedan, SUV, or Wagon)

Class

BEV= all electric, PHEV=plug-in hybrid, Hybrid=hybrid

LowPrice

Lowest MSRP (in $1,000)

HighPrice

Highest MSRP (in $1,000)

Seating

Seating capacity

Acc030

Time (in seconds) to go from 0 to 30 mph

Acc060

Time (in seconds) to go from 0 to 60 mph

QtrMile

Time (in seconds) to go ¼ mile

Braking

Distance to stop from 60 mph (dry pavement)

MPKWH

Miles per Kilowatt hour of elctricity

MPGE

Miles per gallon of gas equivalent

MPG

Miles per gallon when using gas

RangeE

Range when using battery only

RangeG

Range when using gas

Battery

Size of battery (in kWh)

FuelCap

Gas fuel capacity (in gallons)

Length

Length (in inches)

Width

Width (in inches)

Height

Height (in inches)

Wheelbase

Wheelbase (in inches)

UTurn

Diameter (in feet) needed for a U-turn

Weight

Curb weight (in pounds)

CRType

Consumer report classification: Car, Luxury, Luxury SUV, Minivan, Pickup, SUV, SUV-3Row

Details

Data for a set of 93 new electric, plug-in hybride, or hybrid car models in 2025 based on information in Consumer Reports.

Source

Data on new car models in 2025 accessed from Consumer Reports website. https://www.consumerreports.org/cars/

Boston Celtics Basketball (2024)

Description

Game log data for the Boston Celticss basketball team in 2023-2024 regular season

Format

A data frame with 82 observations on the following 33 variables.

Game

ID number for each game

Date

Date the game was played (mm/dd/yyy)

Location

Away or Home

Opp

Opponent team

Win

Game result: L or W

Points

Number of points scored

FG

Field goals made

FGA

Field goals attempted

FG3

Three-point field goals made

FG3A

Three-point field goals attempted

FT

Free throws made

FTA

Free throws attempted

Rebounds

Total rebounds

OffReb

Offensive rebounds

Assists

Number of assists

Steals

Number of steals

Blocks

Number of shots blocked

Turnovers

Number of turnovers

Fouls

Number of fouls

OppPoints

Opponent's points scored

OppFG

Opponent's field goals made

OppFGA

Opponent's field goals attempted

OppFG3

Opponent's three-point field goals made

OppFG3A

Opponent's three-point field goals attempted

OppFT

Opponent's free throws made

OppFTA

Opponent's free throws attempted

OppRebounds

Opponent's total rebounds

OppOffReb

Opponent's offensive rebounds

OppAssists

Opponent's assists

OppSteals

Opponent's steals

OppBlocks

Opponent's shots blocked

OppTurnovers

Opponent's turnovers

OppFouls

Opponent's fouls

Details

Information from online boxscores for all 82 regular season games played by the Boston Celtics basketball team during the 2023-2024 season.
** Updated for 4e (earlier versions for the Golden State Warriors are GSWarriors2019 and GSWarriors2016. The 1e version is MiamiHeat dataset from 2011.) **

Source

Data for the 2023-2024 Boston Celtics games downloaded from https://www.basketball-reference.com/teams/BOS/2024/gamelog/ (March 2025)

Breakfast Cereals

Description

Nutrition information for a sample of 30 breakfast cereals

Format

A dataset with 30 observations on the following 10 variables.

Details

Nutrition contents for a sample of breakfast cereals, derived from nutrition labels. Values are per cup of cereal (rather than per serving).

Source

Cereal data obtained from nutrition labels at
http://www.nutritionresource.com/foodcomp2.cfm?id=0800

City Temperatures

Description

Mean monthly temperature in Moscow, Melbourne, and San Francisco for 2023 and 2024

Format

A data frame with 24 observations on the following 5 variables.

Year

2023 or 2024

Month

1=January through 12=December

Moscow

Monthly temperatures in Moscow (Russia)

Melbourne

Monthly temperatures in Melbourne (Australia)

SanFrancisco

Monthly temperatures in San Francisco (United States)

Details

Mean monthly temperatures in degrees C for the years 2023 and 2024 in each of three cities.
** Updated for 4e (earlier versions for 2017 and 2018 in CityTemps3e, for 2014 and 2015 in CityTemps2e). **

Source

Source: https://www.weatherandclimate.info/history/ add station codes 94866 (Melbourne), 72494 (San Francisco), 27612 (Moscow) to url.

City Temperatures - 2e

Description

Mean monthly temperature in Moscow, Melbourne, and San Francisco for 2014 and 2015

Format

A dataset with 24 observations on the following 5 variables.

Details

Mean monthly temperatures in degrees Celsius for the years 2014 and 2015 in each of three cities.
** From 2e - dataset has been updated for 3e **

Source

KNMI Climate Explorer at https://climexp.knmi.nl/selectstation.cgi?id=someone@somewhere

City Temperatures - 3e

Description

Mean monthly temperature in Moscow, Melbourne, and San Francisco for 2017 and 2018

Format

A data frame with 24 observations on the following 5 variables.

Year

2017 or 2018

Month

1=January through 12=December

Moscow

Monthly temperatures in Moscow (Russia)

Melbourne

Monthly temperatures in Melbourne (Australia)

San.Francisco

Monthly temperatures in San Francisco (United States)

Details

Mean monthly temperatures in degrees C for the years 2017 and 2018 in each of three cities.
** Updated for 3e (an earlier version for 2014 and 2015 is at CityTemps2e). **

Source

Source: KNMI Climate Explorer at https://climexp.knmi.nl/selectstation.cgi?id=someone@somewhere Use station codes 94866 (Melbourne), 72494 (San Francisco), 27612 (Moscow).

Cocaine Treatment

Description

Relapse/no relapse responses to three different treatments for cocaine addiction

Format

A dataset with 72 observations on the following 2 variables.

Details

Data from an experiment to investigate the effectiveness of the two drugs, desipramine and lithium, in the treatment of cocaine addiction. Subjects (cocaine addicts seeking treatment) were randomly assigned to take one of the treatment drugs or a placebo. The response variable is whether or not the subject relapsed (went back to using cocaine) after the treatment.

Source

Gawin, F., et.al., "Desipramine Facilitation of Initial Cocaine Abstinence", Archives of General Psychiatry, 1989; 46(2): 117 - 121.

Cola Calcium

Description

Calcium excretion with diet cola and water

Format

A dataset with 16 observations on the following 2 variables.

Details

A sample of 16 healthy women aged 18 - 40 were randomly assigned to drink 24 ounces of either diet cola or water. Their urine was collected for three hours after ingestion of the beverage and calcium excretion (in mg.) was measured . The researchers were investigating whether diet cola leaches calcium out of the system, which would increase the amount of calcium in the urine for diet cola drinkers.

Source

Larson, Amin, Olsen, and Poth, Effect of Diet Cola on Urine Calcium Excretion, Endocrine Reviews, 31[3]: S1070, June 2010. These data are recreated from the published summary statistics, and are estimates of the actual data.

College Experience (2021-2022)

Description

Measures on college students in the 2021-2022 school year

Format

A data frame with 79 observations on the following 13 variables. Values are averages over reports throughout the year for each student.

iOS

Indicator for whether the student is an iOS user (1) or an Android user (0)

Still

Time spent still (no movement) in seconds

Steps

Number of steps per day

PhoneUnlocked

Amount of time that a student uses their phone in unlocked state (i.e., total phone usage duration)

PhoneProportion

Proportion of waking hours that a student spends with their phone unlocked

Sleep

Sleep duration (based on a predictive model) in hours

Anxious

Over the last 2 weeks, how often have you been bothered by the following problems? Feeling nervous, anxious or on edge (0: Not at all; 1: Several days; 2: More than half the days; 3: Nearly every day)

Depressed

Over the last 2 weeks, how often have you been bothered by the following problems? Feeling down, depressed or hopeless (0: Not at all; 1: Several days; 2: More than half the days; 3: Nearly every day)

Social

Have you spent most of your time alone or with others today? (1: Almost always alone; 2: Mostly alone, a little time with others; 3: Equal amounts of time alone and with others; 4: Mostly with others, a little time alone; 5: Almost always with others)

FeelGood

Right now, Overall, I feel good about myself (1: Not at All; 2: A Little Bit; 3: Somewhat; 4: Very Much; 5: Extremely)

Stress

Are you feeling stressed now? (1: Not at All; 2: A Little Bit; 3: Somewhat; 4: Very Much; 5: Extremely)

Sex

Self-reported sex of the participant (F or M)

AnxiousBinary

1 if the value for Anxious is > 0, 0 if the value is 0.

Details

College students allowed researchers to collect live data readily accessible from their smartphones (such as data on phone usage, physical activity, and sleep) for the duration of their time at college. These students also regularly assessed their own mental health and well-being via surveys. This dataset contains each student's average values for the 2021-2022 academic year.

Source

Subigya Nepal, et. al. "Capturing the College Experience: A Four-Year Mobile Sensing Study of Mental Health, Resilience, and Behavior of College Students during the Pandemic", Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 8, 1, Article 38 (March 2024).

College Scorecard

Description

Information on all US post-secondary schools collected by the Department of Education for the College Scorecard

Format

A data frame with 5702 observations on the following 35 variables.

Name

Name of the school

State

State where school is located

ID

ID number for school

Main

Main campus? (1=yes, 0=branch campus)

Accred

Accreditation agency

MainDegree

Predominant undergrad degree (0=not classified, 1=certificate, 2=associate, 3=bachelors,4=only graduate)

HighDegree

Highest degree (0=no degrees, 1=certificate, 2=associate, 3=bachelors, 4= graduate)

Control

Control of school (Private, Profit, Public)

Region

Region of country (Midwest, Northeast, Southeast, Territory, West)

Locale

Locale (City, Rural, Suburb, Town)

Latitude

Latitude

Longitude

Longitude

AdmitRate

Admission rate

MidACT

Median of ACT scores

AvgSAT

Average combined SAT equivalent scores for admitted students

Online

Only online (distance) programs

Enrollment

Undergraduate enrollment

White

Percent of undergraduates who report being white

Black

Percent of undergraduates who report being black

Hispanic

Percent of undergraduates who report being Hispanic

Asian

Percent of undergraduates who report being Asian

Other

Percent of undergraduates who don't report one of the above

PartTime

Percent of undergraduates who are part-time students

NetPrice

Average net price (cost minus aid)

Cost

Average total cost for tuition, room, board, etc.

TuitionIn

In-state tuition and fees

TuitionOut

Out-of-state tuition and fees

TuitionFTE

Net Tuition revenue per FTE student

InstructFTE

Instructional spending per FTE student

FacSalary

Average monthly salary for full-time faculty

FullTimeFac

Percent of faculty that are full-time

Pell

Percent of students receiving Pell grants

CompRate

Completion rate (percent who finish program within 150% of normal time)

Debt

Median debt for students who complete program

PctWomen

Percent of women students

Details

The US Department of Education maintains a database through its College Scorecard project of demographic information from all active postsecondary educational institutions that participate in Title IV. This dataset contains a small subset of the variables in the full College Scorecard. Schools with missing or zero enrollment were omitted. Updated for 4e (previous dataset is now CollegeScores3e).

Source

Data downloaded from the US Department of Education's College Scorecard at https://collegescorecard.ed.gov/data/ (February 2025)

College Scorecard - Two Year

Description

Information on all US colleges and universities that primarily grant associate's degrees, collected by the Department of Education for the College Scoreboard.

Format

A data frame with 1037 observations on the following 35 variables.

Name

Name of the school

State

State where school is located

ID

ID number for school

Main

Main campus? (1=yes, 0=branch campus)

Accred

Accreditation agency

MainDegree

Predominant undergrad degree (2=associate)

HighDegree

Highest degree (0=no degrees, 1=certificate, 2=associate, 3=bachelors, 4= graduate)

Control

Control of school (Private, Profit, Public)

Region

Region of country (Midwest, Northeast, Southeast, Territory, West)

Locale

Locale (City, Rural, Suburb, Town)

Latitude

Latitude

Longitude

Longitude

AdmitRate

Admission rate

MidACT

Median of ACT scores

AvgSAT

Average combined SAT equivalent scores for admitted students

Online

Only online (distance) programs

Enrollment

Undergraduate enrollment

White

Percent of undergraduates who report being white

Black

Percent of undergraduates who report being black

Hispanic

Percent of undergraduates who report being Hispanic

Asian

Percent of undergraduates who report being Asian

Other

Percent of undergraduates who don't report one of the above

PartTime

Percent of undergraduates who are part-time students

NetPrice

Average net price (cost minus aid)

Cost

Average total cost for tuition, room, board, etc.

TuitionIn

In-state tuition and fees

TuitionOut

Out-of-state tuition and fees

TuitionFTE

Net Tuition revenue per FTE student

InstructFTE

Instructional spending per FTE student

FacSalary

Average monthly salary for full-time faculty

FullTimeFac

Percent of faculty that are full-time

Pell

Percent of students receiving Pell grants

CompRate

Completion rate (percent who finish program within 150% of normal time)

Debt

Median debt for students who complete program

PctWomen

Percent of women students

Details

The US Department of Education maintains a database through its College Scorecard project of demographic information from all active postsecondary educational institutions that participate in Title IV. This dataset contains a small subset of the variables in the full College Scorecard and only the schools that primarily grant associate's degrees (MainDegree=2). The CollegeScores dataset contains these and other schools with other degree types. Schools with missing or zero enrollment were omitted. Updated for 4e (previous dataset is now CollegeScores2yr3e).

Source

Data downloaded from the US Department of Education's College Scorecard at https://collegescorecard.ed.gov/data/ (February 2025)

College Scorecard - Two Year- 3e

Description

Information on all US colleges and universities that primarily grant associate's degrees, collected by the Department of Education for the College Scoreboard.

Format

A data frame with 1141 observations on the following 37 variables.

Name

Name of the school

State

State where school is located

ID

ID number for school

Main

Main campus? (1=yes, 0=branch campus)

Accred

Accreditation agency

MainDegree

Predominant undergrad degree (2=associate)

HighDegree

Highest degree (0=no degrees, 1=certificate, 2=associate, 3=bachelors, 4= graduate)

Control

Control of school (Private, Profit, Public)

Region

Region of country (Midwest, Northeast, Southeast, Territory, West)

Locale

Locale (City, Rural, Suburb, Town)

Latitude

Latitude

Longitude

Longitude

AdmitRate

Admission rate

MidACT

Median of ACT scores

AvgSAT

Average combined SAT scores

Online

Only online (distance) programs

Enrollment

Undergraduate enrollment

White

Percent of undergraduates who report being white

Black

Percent of undergraduates who report being black

Hispanic

Percent of undergraduates who report being Hispanic

Asian

Percent of undergraduates who report being Asian

Other

Percent of undergraduates who don't report one of the above

PartTime

Percent of undergraduates who are part-time students

NetPrice

Average net price (cost minus aid)

Cost

Average total cost for tuition, room, board, etc.

TuitionIn

In-state tuition and fees

TuitonOut

Out-of-state tuition and fees

TuitionFTE

Net Tuition revenue per FTE student

InstructFTE

Instructional spending per FTE student

FacSalary

Average monthly salary for full-time faculty

FullTimeFac

Percent of faculty that are full-time

Pell

Percent of students receiving Pell grants

CompRate

Completion rate (percent who finish program within 150% of normal time)

Debt

Average debt for students who complete program

Female

Percent of female students

FirstGen

Percent of first-generation students

MedIncome

Median family income (in $1,000)

Details

The US Department of Education maintains a database through its College Scorecard project of demographic information from all active postsecondary educational institutions that participate in Title IV. This dataset contains a small subset of the variables in the full College Scorecard and only the schools that primarily grant associate's degrees (MainDegree=2). The CollegeScores dataset contains these and other schools with other degree types.

Source

Data downloaded from the US Department of Education's College Scorecard at https://collegescorecard.ed.gov/data/ (November 2019)

College Scorecard - 3e

Description

Information on all US post-secondary schools collected by the Department of Education for the College Scorecard

Format

A data frame with 6141 observations on the following 37 variables.

Name

Name of the school

State

State where school is located

ID

ID number for school

Main

Main campus? (1=yes, 0=branch campus)

Accred

Accreditation agency

MainDegree

Predominant undergrad degree (0=not classified, 1=certificate, 2=associate, 3=bachelors,4=only graduate)

HighDegree

Highest degree (0=no degrees, 1=certificate, 2=associate, 3=bachelors, 4= graduate)

Control

Control of school (Private, Profit, Public)

Region

Region of country (Midwest, Northeast, Southeast, Territory, West)

Locale

Locale (City, Rural, Suburb, Town)

Latitude

Latitude

Longitude

Longitude

AdmitRate

Admission rate

MidACT

Median of ACT scores

AvgSAT

Average combined SAT scores

Online

Only online (distance) programs

Enrollment

Undergraduate enrollment

White

Percent of undergraduates who report being white

Black

Percent of undergraduates who report being black

Hispanic

Percent of undergraduates who report being Hispanic

Asian

Percent of undergraduates who report being Asian

Other

Percent of undergraduates who don't report one of the above

PartTime

Percent of undergraduates who are part-time students

NetPrice

Average net price (cost minus aid)

Cost

Average total cost for tuition, room, board, etc.

TuitionIn

In-state tuition and fees

TuitonOut

Out-of-state tuition and fees

TuitionFTE

Net Tuition revenue per FTE student

InstructFTE

Instructional spending per FTE student

FacSalary

Average monthly salary for full-time faculty

FullTimeFac

Percent of faculty that are full-time

Pell

Percent of students receiving Pell grants

CompRate

Completion rate (percent who finish program within 150% of normal time)

Debt

Average debt for students who complete program

Female

Percent of female students

FirstGen

Percent of first-generation students

MedIncome

Median family income (in $1,000)

Details

The US Department of Education maintains a database through its College Scorecard project of demographic information from all active postsecondary educational institutions that participate in Title IV. This dataset contains a small subsets of the variables in the full College Scorecard.

Source

Data downloaded from the US Department of Education's College Scorecard at https://collegescorecard.ed.gov/data/ (November 2019)

College Scorecard - Four Year

Description

Information on all US colleges and universities that primarily grant bachelor's degrees, collected by the Department of Education for the College Scoreboard

Format

A data frame with 2007 observations on the following 35 variables.

Name

Name of the school

State

State where school is located

ID

ID number for school

Main

Main campus? (1=yes, 0=branch campus)

Accred

Accreditation agency

MainDegree

Predominant undergrad degree (3=bachelors)

HighDegree

Highest degree (0=no degrees, 1=certificate, 2=associate, 3=bachelors, 4= graduate)

Control

Control of school (Private, Profit, Public)

Region

Region of country (Midwest, Northeast, Southeast, Territory, West)

Locale

Locale (City, Rural, Suburb, Town)

Latitude

Latitude

Longitude

Longitude

AdmitRate

Admission rate

MidACT

Median of ACT scores

AvgSAT

Average combined SAT equivalent scores for admitted students

Online

Only online (distance) programs

Enrollment

Undergraduate enrollment

White

Percent of undergraduates who report being white

Black

Percent of undergraduates who report being black

Hispanic

Percent of undergraduates who report being Hispanic

Asian

Percent of undergraduates who report being Asian

Other

Percent of undergraduates who don't report one of the above

PartTime

Percent of undergraduates who are part-time students

NetPrice

Average net price (cost minus aid)

Cost

Average total cost for tuition, room, board, etc.

TuitionIn

In-state tuition and fees

TuitionOut

Out-of-state tuition and fees

TuitionFTE

Net Tuition revenue per FTE student

InstructFTE

Instructional spending per FTE student

FacSalary

Average monthly salary for full-time faculty

FullTimeFac

Percent of faculty that are full-time

Pell

Percent of students receiving Pell grants

CompRate

Completion rate (percent who finish program within 150% of normal time)

Debt

Median debt for students who complete program

PctWomen

Percent of women students

Details

The US Department of Education maintains a database through its College Scorecard project of demographic information from all active postsecondary educational institutions that participate in Title IV. This dataset contains a small subset of the variables in the full College Scorecard and only the schools that primarily grant bachelor's degrees (MainDegree=3). The CollegeScores dataset contains these and other schools with other degree types. Schools with missing or zero enrollment were omitted. Updated for 4e (previous dataset is now CollegeScores4yr3e).

Source

Data downloaded from the US Department of Education's College Scorecard at https://collegescorecard.ed.gov/data/ (February 2025)

College Scorecard - Four Year - 3e

Description

Information on all US colleges and universities that primarily grant bachelor's degrees, collected by the Department of Education for the College Scoreboard

Format

A data frame with 2012 observations on the following 37 variables.

Name

Name of the school

State

State where school is located

ID

ID number for school

Main

Main campus? (1=yes, 0=branch campus)

Accred

Accreditation agency

MainDegree

Predominant undergrad degree (3=bachelors)

HighDegree

Highest degree (0=no degrees, 1=certificate, 2=associate, 3=bachelors, 4= graduate)

Control

Control of school (Private, Profit, Public)

Region

Region of country (Midwest, Northeast, Southeast, Territory, West)

Locale

Locale (City, Rural, Suburb, Town)

Latitude

Latitude

Longitude

Longitude

AdmitRate

Admission rate

MidACT

Median of ACT scores

AvgSAT

Average combined SAT scores

Online

Only online (distance) programs

Enrollment

Undergraduate enrollment

White

Percent of undergraduates who report being white

Black

Percent of undergraduates who report being black

Hispanic

Percent of undergraduates who report being Hispanic

Asian

Percent of undergraduates who report being Asian

Other

Percent of undergraduates who don't report one of the above

PartTime

Percent of undergraduates who are part-time students

NetPrice

Average net price (cost minus aid)

Cost

Average total cost for tuition, room, board, etc.

TuitionIn

In-state tuition and fees

TuitonOut

Out-of-state tuition and fees

TuitionFTE

Net Tuition revenue per FTE student

InstructFTE

Instructional spending per FTE student

FacSalary

Average monthly salary for full-time faculty

FullTimeFac

Percent of faculty that are full-time

Pell

Percent of students receiving Pell grants

CompRate

Completion rate (percent who finish program within 150% of normal time)

Debt

Average debt for students who complete program

Female

Percent of female students

FirstGen

Percent of first-generation students

MedIncome

Median family income (in $1,000)

Details

The US Department of Education maintains a database through its College Scorecard project of demographic information from all active postsecondary educational institutions that participate in Title IV. This dataset contains a small subset of the variables in the full College Scorecard and only the schools that primarily grant bachelor's degrees (MainDegree=3). The CollegeScores dataset contains these and other schools with other degree types.

Source

Data downloaded from the US Department of Education's College Scorecard at https://collegescorecard.ed.gov/data/ (November 2019)

Commute Atlanta

Description

Commute times and distances for a sample of 500 people in Atlanta

Format

A data frame with 500 observations on the following 5 variables.

Details

Data from the US Census Bureau's American Housing Survey (AHS) which contains information about housing and living conditions for samples from certain metropolitan areas. These data were extracted from respondents in the Atlanta metropolitan area. They include only cases where the respondent worked somewhere other than home. Values show the time (in minutes) and distance (in miles) that respondents typically traveled on their commute to work each day as well as age and sex.

Source

Sample chosen using DataFerret at http://www.thedataweb.org/index.html.

Commute Times in St. Louis

Description

Commute times and distances for a sample of 500 people in St. Louis

Format

A dataset with 500 observations on the following 5 variables.

Details

Data from the US Census Bureau's American Housing Survey (AHS) which contains information about housing and living conditions for samples from certain metropolitan areas. These data were extracted from respondents in the St. Louis metropolitan area. They include only cases where the respondent worked somewhere other than home. Values show the time (in minutes) and distance (in miles) that respondents typically traveled on their commute to work each day as well as age and sex.

Source

Sample chosen using DataFerret at http://www.thedataweb.org/index.html.

Compassionate Rats

Description

Would a rat attempt to free a trapped rat?

Format

A dataset with 30 observations on the following 2 variables.

Details

In a recent study, some rats showed compassion by freeing another trapped rat, even when chocolate served as a distraction and even when the rats would then have to share the chocolate with their freed companion.

Source

Bartal I.B., Decety J., and Mason P., "Empathy and Pro-Social Behavior in Rats," Science, 2011; 224(6061):1427-1430.

Cricket Chirps

Description

Cricket chirp rate and temperature

Format

A dataset with 7 observations on the following 2 variables.

Details

The data were collected by E.A. Bessey and C.A. Bessey who measured chirp rates for crickets and temperatures during the summer of 1898.

Source

From E.A Bessey and C.A Bessey, Further Notes on Thermometer Crickets, American Naturalist, (1898) 32, 263-264.

Developmental Services

Description

Funding for individuals by the California Department of Developmental Services (DDS),

Format

A dataset with 1000 observations on the following 6 variables.

Details

The California Department of Developmental Services (DDS) allocates funds to support developmentally disabled California residents (such as those with autism, cerebral palsy, or intellectual disabilities) and their families. We refer to those supported by DDS as DDS consumers. The dataset DDS includes data on annual expenditure (in $), ethnicity, age, and gender for 1000 DDS consumers.

Source

Taylor, S.A. and Mickel, A. E. (2014). "Simpson's Paradox: A Data Set and Discrimination Case Study Exercise," Journal of Statistics Education, 22(1). The dataset has been altered slightly for privacy reasons, but is based on actual DDS consumers.

December Flights

Description

Difference between actual and scheduled arrival for United and Delta flights in December 2024.

Format

A data frame with 2000 observations on the following 2 variables.

Airline

Delta or United

Difference

Actual - Scheduled arrival times (in minutes)

Details

For a sample of 1000 December flights (in 2024) from each airline, we find the difference between actual and scheduled arrival times. A negative value indicates the flight arrived early.
** Updated for 4e (earlier versions are DecemberFlights3e from 2018 and DecemberFlights2e from 2014.)

Source

Downloaded from the Bureau of Transportation Statistics (https://www.transtats.bts.gov/).

December Flights - 2014

Description

Difference between actual and scheduled arrival for a sample of United and Delta flights in December 2014.

Format

A dataset with 2000 observations on the following 2 variables.

Details

For a sample of 1000 December flights (in 2014) from each airline, we find the difference between actual and scheduled arrival times. A negative value indicates the flight arrived early.
** From 2e - dataset has been updated for 3e **

Source

Downloaded from the Bureau of Transportation Statistics (https://www.bts.gov/). More specific URL is https://www.transtats.bts.gov/DL_SelectFields.asp?Table_ID=236&DB_Short_Name=On-Time.

December Flights - 2018

Description

Difference between actual and scheduled arrival for United and Delta flights in December 2018.

Format

A data frame with 2000 observations on the following 2 variables.

Airline

Delta or United

Difference

Actual - Scheduled arrival times (in minutes)

Details

For a sample of 1000 December flights (in 2018) from each airline, we find the difference between actual and scheduled arrival times. A negative value indicates the flight arrived early.
** Updated for 3e (earlier version from 2014 is in DecemberFlights2e.)

Source

Downloaded from the Bureau of Transportation Statistics (https://www.transtats.bts.gov/).

Diet and Depression

Description

Results from a study of a short-term diet intervention on depression.

Format

A data frame with 75 observations on the following 10 variables.

Group

Control or Diet

CESD1

CESD depression score on Day 1

CESD21

CESD depression score on Day 21

CESDDiff

Change in CESD depression score

DASS1

DASS depression score on Day 1

DASS21

DASS depression score on Day 21

DASSDiff

Change in DASS depression score

BMI1

Body Mass Index on Day 1

BMI21

Body Mass Index on Day 21

BMIDiff

Change in Body Mass Index

Details

A group of researchers in Australia conducted a short (three-week) dietary intervention in a randomized controlled experiment. In the study, 75 college-age students with elevated depression symptoms and relatively poor diet habits were randomly assigned to either a healthy diet intervention group or a control group. The researchers recorded the change over the three-week period on two different numeric scales of depression (the CESD scale and the DASS scale). The CESD (Centre for Epidemiological Studies Depression) score is based more on clinical observations, while the DASS (Depression, Anxiety, and Stress Scale) depends more on self-reported information. They also recorded body mass index (BMI) at the start and end of the 21 day period.

Source

Francis HM, et al., "A brief diet intervention can reduce symptoms of depression in young adults - A randomised controlled trial," PLoS ONE, 14(10), October 2019.

Digit Counts

Description

Digits from social security numbers and student selected "random numbers"

Format

A dataset with 150 observations on the following 7 variables.

Details

A sample of students were asked to give a random four digit number. The numbers are given in the dataset, along with separate columns for each of the four digits. The data also show the last two digits of each student's social security number (SSN).

Source

In-class student surveys from several classes.

Dog/Owner matches

Description

Experiment to match dogs with owners

Format

A dataset with 25 observations on the following variable.

Details

Pictures were taken of 25 owners and their purebred dogs, selected from dog parks. Study participants were shown a picture of an owner together with pictures of two dogs (the owner's dog and another random dog from the study) and asked to choose which dog most resembled the owner. Each dog-owner pair was viewed by 28 naive undergraduate judges, and the pairing was deemed "correct" (yes) if the majority of judges (more than 14) chose the correct dog to go with the owner.
** In first edition, but not as dataset in 2e **

Source

Roy and Christenfeld, Do Dogs Resemble their Owners?, Psychological Science, Vol. 15, No. 5, 2004, pp. 361 - 363.

Drug Resistance

Description

Effect on drug resistance by level of treatment in mice.

Format

A dataset with 72 observations on the following 5 variables.

Details

In an experiment to study drug resistance in mice, groups of 18 mice were injected with a mixture of drug-resistant and drug-susceptible malaria parasites. One group received no treatment while the others got limited, moderate, or aggressive amounts of anti-malarial treatment. The weight and red blood cell density reflect the initial health of the mice. Density of resistant parasites and number of days infectious measure the effectiveness of the treatment.

Source

Huijben S, Bell AS, Sim DG, Tomasello D, Mideo N, Day T, Read AF (2013) Aggressive chemotherapy and the selection of drug resistant pathogens. PLoS Pathogens 9(9): e1003578.
http://dx.doi.org/10.1371/journal.ppat.1003578
Huijben S, et al., (2013). Data from: Aggressive chemotherapy and the selection of drug resistant pathogens. Dryad Digital
Repository. http://dx.doi.org/10.5061/dryad.09qc0

Education and Literacy

Description

Education spending and literacy rates for countries.

Format

A data frame with 193 observations on the following 4 variables.

Country

Name of country

Code

Three-letter code for country

Education

Education spending (as a percentage of GDP)

Literacy

Literacy rate

Details

For each country, we have public spending on education (as a percentage of GDP) and literacy rate (percentage of the adult population who can read and write).
** Updated for 4e (an earlier versions are at EducationLiteracy2e and EducationLiteracy2e). **

Source

Most recent data (as of 2024) for each country obtained from https://www.worldbank.org/ext/en/home.

Education Literacy - 2015

Description

Education spending and literacy rates for countries.

Format

A dataset with 188 observations on the following 3 variables.

Details

For each country, we have public spending on education (as a percentage of GDP) and literacy rate (percentage of the population who can read and write).
** From 2e - dataset has been updated for 3e **

Source

Most recent data (as of 2015) for each country obtained from worldbank.org and http:\www.knoema.com

Education and Literacy - 2019

Description

Education spending and literacy rates for countries.

Format

A data frame with 170 observations on the following 4 variables.

Country

Name of country

Code

Three-letter code for country

Education

Education spending (as a percentage of GDP)

Literacy

Literacy rate

Details

For each country, we have public spending on education (as a percentage of GDP) and literacy rate (percentage of the population who can read and write).
** Updated for 3e (an earlier version is at EducationLiteracy2e). **

Source

Most recent data (as of 2019) for each country obtained from https://www.worldbank.org/ext/en/home.

Election Margin

Description

Approval rating and election margin for recent presidential elections

Format

A dataset with 13 observations on the following 5 variables.

Details

Data include US Presidential elections since 1940 in which an incumbent was running for president. The approval rating for the sitting president is compared to the margin of victory/defeat in the election.
** Updated for 4e with 2020 election, 2e added 2012 election **

Source

Silver, Nate, "Approval Ratings and Re-Election Odds", fivethirtyeight.com, posted January 28, 2011 and http:\realclearpolitics.org

Election Margin 1940-2012

Description

Approval rating and election margin for recent US presidential elections with an incumbent president

Format

A dataset with 12 observations on the following 5 variables.

Details

Data include US Presidential elections since 1940 in which an incumbent was running for president. The approval rating for the sitting president is compared to the margin of victory/defeat in the election.

Source

Silver, Nate, "Approval Ratings and Re-Election Odds", fivethirtyeight.com, posted January 28, 2011 and http:\realclearpolitics.org

Employed in American Community Survey - 2023

Description

Employed individuals from the American Community Survey (ACS) dataset

Format

A data frame with 5862 observations on the following 9 variables.

Sex

0=female and 1=male

Age

Age (years)

Married

0=not married and 1=married

Income

Wages and salary for the past 12 months (in $1,000's)

HoursWk

Hours of work per week

Race

asian, black, other, white

USCitizen

1=citizen and 0=noncitizen

HealthInsurance

1=have health insurance and 0= no health insurance

Language

1=native English speaker and 0=other

Details

This is a subset of the ACS dataset from 2023 including only 5862 individuals who were employed. (HoursWk>0)
** Updated for 4e (an earlier versions are EmployedACS2017 and EmployedACS2010). **

Source

The full public dataset can be downloaded at https://www.census.gov/programs-surveys/acs/microdata.html, and the full list of variables are at https://www.census.gov/programs-surveys/acs/microdata/documentation.html

Specific request for these variables is https://data.census.gov/app/mdat/ACSPUMS1Y2023/table?cv=SEX,MAR,RAC1P,HICOV&vv=AGEP,WAGP,WKHP&rv=CIT,LANX&wt=PWGTP

Employed in American Community Survey - 2010

Description

Employed individuals from the American Community Survey (ACS) dataset in 2010

Format

A dataset with 431 observations on the following 9 variables.

Details

This is a subset of the ACS dataset including only 431 individuals who were employed.
** From 2e - dataset has been updated for 3e **

Source

The full public dataset can be downloaded at
http://www.census.gov/acs/www/data documentation/pums data/,
and the full list of variables are at
http://www.census.gov/acs/www/Downloads/data documentation/pums/DataDict/PUMSDataDict10.pdf

Employed in American Community Survey - 2017

Description

Employed individuals from the American Community Survey (ACS) dataset

Format

A data frame with 1287 observations on the following 9 variables.

Sex

0=female and 1=male

Age

Age (years)

Married

0=not married and 1=married

Income

Wages and salary for the past 12 months (in $1,000's)

HoursWk

Hours of work per week

Race

asian, black, other, white

USCitizen

1=citizen and 0=noncitizen

HealthInsurance

1=have health insurance and 0= no health insurance

Language

1=native English speaker and 0=other

Details

This is a subset of the ACS dataset (2017) including only 1287 individuals who were employed. (HoursWk>0).
** Updated for 3e (an earlier version is at EmployedACS2010). **

Source

The full public dataset can be downloaded at https://www.census.gov/programs-surveys/acs/microdata/access.html, and the full list of variables is at https://www.census.gov/programs-surveys/acs/microdata.html

Exercise Hours

Description

Amount of exercise per week for students (and other variables)

Format

A data frame with 50 observations on the following 7 variables.

Year

Year in school (1=First year,..., 4=Senior)

Sex

F or M

Hand

Left (l) or Right (r) handed?

Exercise

Hours of exercise per week

TV

Hours of TV viewing per week

Pulse

Resting pulse rate (beats per minute)

Pierces

Number of body piercings

Details

Data from an in-class survey of statistics students asking about amount of exercise, TV viewing, handedness, sex, pulse rate, and number of body piercings. Note the Sex variable was labeled as Gender in earlier versions of this dataset. We acknowledge that this binary dichotomization is not a complete or inclusive representation of reality.

Source

In-class student survey.

Facebook Friends

Description

Data on number of Facebook friends and grey matter density in brain regions related to social perception and associative memory.

Format

A dataset with 40 observations on the following 2 variables.

Details

A recent study in Great Britain examines the relationship between the number of friends an individual has on Facebook and grey matter density in the areas of the brain associated with social perception and associative memory. The study included 40 students at City University London.

Source

Kanai, R., Bahrami, B., Roylance, R., and Rees, G., "Online social network size is reflected in human brain structure," Proceedings of the Royal Society, 7 April 2012; 279(1732): 1327-1334. Data approximated from information in the article.

Fat Mice 18

Description

Weight gain for mice with different nighttime light conditions

Format

A dataset with 18 observations on the following 2 variables.

Details

This is a subset of the LightatNight dataset, showing body mass gain in mice after 4 weeks for two of the treatment conditions: a normal light/dark cycle (LD) or a bright light on at night (LL).
** In first edition, but not 2e **

Source

Fonken, L., et. al., "Light at night increases body mass by shifting time of food intake," Proceedings of the National Academy of Sciences, October 26, 2010; 107(43): 18664-18669.

Fire Ants

Description

Reactions of lizards to the presence of fire ants.

Format

A dataset with 80 observations on the following 3 variables.

Details

The red imported fire ant, Solenopsis invicta, is native to South America, but has an expansive invasive range, including much of the southern United States (invasion of this ant is predicted to go global). In the United States, these ants occupy similar habitats as fence lizards. The ants eat the lizards and the lizards eat the ants, and in either scenario the venom from the fire ant can be fatal to the lizard. The study explored the question of whether lizards learn to adapt their behavior if their environment has been invaded by fire ants by taking lizards from an uninvaded habitat (eastern Arkansas) and lizards from an invaded habitat (southern Alabama, which has been invaded for more than 70 years), exposing them to fire ants, and measuring how long it takes each lizard to flee and the number of twitches each lizard does.

Source

Langkilde, T. (2009). "Invasive fire ants alter behavior and morphology of native lizards"", Ecology, 90(1): 208-217. Thanks to Dr. Langkilde for providing the data.

Fish Respiration and Calcium - Full Data

Description

An experiment to look at fish respiration rates in water with different levels of calcium.

Format

A dataset with 360 observations on the following 2 variables.

Details

Fish were randomly assigned to twelve tanks with different levels (measured in mg/L) of calcium. Respiration rate was measured as number of gill beats per minute.

Source

Thanks to Prof. Brad Baldwin for supplying the data.

Fish Respiration and Calcium

Description

Respiration rate for fish in three levels of calcium.

Format

A dataset with 90 observations on the following 2 variables.

Details

Fish were randomly assigned to three tanks with different levels (low, medium and high) of calcium. Respiration rate was measured as number of gill beats per minute.

Source

Thanks to Prof. Brad Baldwin for supplying the data.

Fisher's Iris Data

Description

Measurements of three iris species

Format

A dataset with 150 observations on the following 5 variables.

Details

Data used in Fisher's 1936 paper, this famous dataset looks at measurements for samples of three different species of iris. The petal is part of the flower itself and the sepals are green leaves, directly under the petals, providing support.

Source

R. A. Fisher (1936). "The use of multiple measurements in taxonomic problems". Annals of Eugenics 7 (2): 179–188. doi:10.1111/j.1469-1809.1936.tb02137.x.

Flight times

Description

Flight times for Flight 179 (Boston-SF) and Flight 180 (SF-Boston).

Format

A dataset with 36 observations on the following 3 variables.

Details

United Airlines Flight 179 was a daily flight from Boston to San Francisco. Flight 180 goes in the other direction (SF to Boston). The data show the airborne flying times for each flight on the three dates each month (5th, 15th and 25th) in 2010.
** In first edition, but not in 2e - replaced by Flight433 **

Source

Data collected from the Bureau of Transportation Statistics website at
http://www.bts.gov/xml/ontimesummarystatistics/src/dstat/OntimeSummaryAirtime.xml

Flight 433 - 2e

Description

Flight times for Flight 433 (Boston-SF) in January 2016.

Format

A dataset with 31 observations on the following 1 variable.

Details

United Airlines Flight 433 was a daily flight from Boston to San Francisco. The data show the airborne flying times for the flight on each day of January 2016.
** From 2e - dataset has been updated for 3e **

Source

Data collected from the Bureau of Transportation Statistics website at
http://www.bts.gov/xml/ontimesummarystatistics/src/dstat/OntimeSummaryAirtime.xml

Flight 433 - 3e

Description

Flight times for Flight 433 (Boston-SF) in January 2019.

Format

A data frame with 28 observations on the following variable.

AirTime

Airborne flying time (in minutes) for Flight 433, Boston to San Francisco

Details

United Airlines Flight 433 was a daily flight from Boston to San Francisco. The data show the airborne flying times for the flight on each day of January 2019.
**Updated for 3e (earlier version from 2016 is in Flight433_2e) **

Source

Data collected from the Bureau of Transportation Statistics website at https://www.transtats.bts.gov/

Flight 475

Description

Flight times for Delta Flight 475 (Boston-SF) in October 2024.

Format

A data frame with 31 observations on the following variable.

AirTime

Airborne flying time (in minutes) for Flight 475, Boston to San Francisco

Details

Delta Airlines Flight 475 was a daily flight from Boston to San Francisco. The data show the airborne flying times for the flight on each day of October 2024.
**Updated for 4e (earlier version are Flight433_3e (2019) and Flight433_2e (2016)) **

Source

Data collected from the Bureau of Transportation Statistics website at https://www.transtats.bts.gov/

Florida Lakes

Description

Water quality measurements for a sample of lakes in Florida

Format

A dataset with 53 observations on the following 12 variables.

Details

This dataset describes characteristics of water and fish samples from 53 Florida lakes. Some variables (e.g. Alkalinity, pH, and Calcium) reflect the chemistry of the water samples. Mercury levels were recorded for a sample of large mouth bass selected at each lake.

Source

Lange, Royals, and Connor, Transactions of the American Fisheries Society (1993)

Football Brain Measurements

Description

Brain measurements for non-football players, football players with no concussion history, and football players with a concussion history.

Format

A dataset with 75 observations on the following 5 variables.

Details

The study included 3 groups, with 25 cases in each group. The control group consisted of healthy individuals with no history of brain trauma who were comparable to the other groups in age, sex, and education. The second group consisted of NCAA Division 1 college football players with no history of concussion, while the third group consisted of NCAA Division 1 college football players with a history of concussion. High resolution MRI was used to collect brain hippocampus volume. Data were collected between June 2011 and August 2013. The data values given here are estimated from information given in the paper.

Source

Singh R, Meier T, Kuplicki R, Savitz J, et al., "Relationship of Collegiate Football Experience and Concussion With Hippocampal Volume and Cognitive Outcome," JAMA, 311(18), 2014

Forest Fires

Description

Characteristics of forest fires in Montesinho park (Portugal)

Format

A data frame with 517 observations on the following 13 variables.

X

West to east coordinates for the site (1=farthest west to 9= farthest east)

Y

North to south coordinates for the site (1=farthest north to 9=farthest south)

Month

Month of the year (jan to dec)

Day

Day of the week (sun to sat)

FFMC

Fine fuel moisture code

DMC

Duff moisture code

DC

Drought code

ISI

Initial spread index

Temp

Outside temperature (in celsius)

RH

Relative humidity (in %)

Wind

Wind speed (in km/h)

Rain

Rain in past 30 minutes (in mm/sq-m)

Area

Total burned area (in hectares)

Details

Data were recorded for fires in the Montesinho natural park in Portugal between January 2000 and December 2003. A map of the park (see the pdf linked below) is divided into 9x9 grid sections (given by the x,y-coordinates in the first two columns of the dataset). There are four components of a Fire Weather Index that rate how weather conditions might increase fire danger. FFMC. DMC, and DC reflect various measures of moisture content, while the ISI score indicated how fast a fire might spread (for example, by wind). For all four measures larger values are associated with more fire danger. Fires that are less than 100 square meters in size (0.01 hectares) are recorded as Area=0.

Source

Data downloaded from the UCI Machine Learning Repository, https://archive.ics.uci.edu/ml/datasets/Forest+Fires
Original article: P. Cortez and A. Morais. "A Data Mining Approach to Predict Forest Fires using Meteorological Data", in New Trends in Artificial Intelligence, Proceedings of the 13th EPIA 2007 - Portuguese Conference on Artificial Intelligence (December 2007).

GPA by Sex

Description

Data from a survey of introductory statistics students.

Format

A dataset with 343 observations on the following 6 variables.

Details

This is a subset of the StudentSurvey dataset where cases with missing values have been dropped and sex is coded as a 0/1 indicator variable.

Source

A first day survey over several different introductory statistics classes.

Golden State Warriors Basketball - 2016

Description

Game log data for the Golden State Warriors basketball team in 2015-2016

Format

A dataset with 82 observations on the following 33 variables.

Details

Information from online boxscores for all 82 regular season games played by the Golden State Warriors basketball team during the 2015-2016 season.
** From 2e - dataset has been updated for 3e **

Source

Data for the 2015-2016 Golden State games downloaded from
http://www.basketball-reference.com/teams/GSW/2016/gamelog/

Golden State Warriors Basketball (2019)

Description

Game log data for the Golden State Warriors basketball team in 2018-2019

Format

A data frame with 82 observations on the following 33 variables.

Game

ID number for each game

Date

Date the game was played (mm/dd/yyy)

Location

Away or Home

Opp

Opponent team

Win

Game result: L or W

Points

Number of points scored

FG

Field goals made

FGA

Field goals attempted

FG3

Three-point field goals made

FG3A

Three-point field goals attempted

FT

Free throws made

FTA

Free throws attempted

Rebounds

Total rebounds

OffReb

Offensive rebounds

Assists

Number of assists

Steals

Number of steals

Blocks

Number of shots blocked

Turnovers

Number of turnovers

Fouls

Number of fouls

OppPoints

Opponent's points scored

OppFG

Opponent's field goals made

OppFGA

Opponent's field goals attempted

OppFG3

Opponent's three-point field goals made

OppFG3A

Opponent's three-point field goals attempted

OppFT

Opponent's free throws made

OppFTA

Opponent's free throws attempted

OppRebounds

Opponent's total rebounds

OppOffReb

Opponent's offensive rebounds

OppAssists

Opponent's assists

OppSteals

Opponent's steals

OppBlocks

Opponent's shots blocked

OppTurnovers

Opponent's turnovers

OppFouls

Opponent's fouls

Details

Information from online boxscores for all 82 regular season games played by the Golden State Warriors basketball team during the 2018-2019 season.
** Updated for third edition (2e version is now GSWarriors2016, 1e version is MiamiHeat dataset) **

Source

Data for the 2018-2019 Golden State games downloaded from https://www.basketball-reference.com/teams/GSW/2019/gamelog/

Genetic Diversity

Description

Genetic diversity for different populations are compared to the distance from East Africa.

Format

A dataset with 52 observations on the following 5 variables.

Details

The data give a measure of genetic diversity for different populations and the geographic distance of each population from East Africa (Addis Ababa, Ethiopia), as one would travel over the surface of the earth by land (migration long ago is thought to have happened by land).

Source

Calculated using data from S Ramachandran, O Deshpande, CC Roseman, NA Rosenberg, MW Feldman, LL Cavalli-Sforza. "Support from the relationship of genetic and geographic distance in human populations for a serial founder effect originating in Africa,"" Proceedings of the National Academy of Sciences, 2005, 102: 15942-15947.

Global Internet Usage - 2010

Description

Internet usage for several countries

Format

A dataset with 9 observations on the following 3 variables.

Details

The Nielsen Company measured connection speeds on home computers in nine different countries. Variables include the percent of internet users with a fast connection (defined as 2Mb/sec or faster) and the average amount of time spent online, defined as total hours connected to the web from a home computer during the month of February 2011.
** From 2e - dataset has been updated for 3e **

Source

NielsenWire, "Swiss Lead in Speed: Comparing Global Internet Connections", April 1, 2011

Global Internet Usage - 2019

Description

Internet usage for several countries

Format

A data frame with 9 observations on the following 3 variables.

Country

Name of country

InternetSpeed

Average download speed (in Mb)

HoursOnline

Average hours online per day

Details

The Worldwide Broadband Speed League tests internet speeds at millions of access points around the world. The average download speed for each country is derived from those data. The DataReportal site provides summaries of country level data on internet usage obtained from various sources. The average number of hours spent online for each country is based on survey data reported at that site.
** Updated for 3e (earlier version from 2011 is at GlobalInternet2011).

Source

Internet speeds for 2019 downloaded from https://bestbroadbanddeals.co.uk/broadband/speed/worldwide-speed-league/
Online hours for 2019 downloaded from https://datareportal.com/library

Global Internet Usage - 2024

Description

Internet usage for several countries in 2024

Format

A data frame with 9 observations on the following 3 variables.

Country

Name of country

InternetSpeed

Average download speed (in Mb)

HoursOnline

Average hours online per day for internet users

Details

The Worldwide Broadband Speed League tests internet speeds at millions of access points around the world. The average download speed for each country is derived from those data. The DataReportal site provides summaries of country level data on internet usage obtained from various sources. The average number of hours spent online for each country is based on survey data reported at that site.
** Updated for 4e (earlier versions are GlobalInternet2019 and GlobalInternet2011).

Source

Internet speeds for 2024 downloaded from https://bestbroadbanddeals.co.uk/broadband/speed/worldwide-speed-league/
Online hours for 2024 downloaded from https://datareportal.com/library

Golf Round

Description

Scorecard for 18 holes of golf

Format

A data frame with 18 observations on the following 4 variables.

Hole

Hole number (1 to 18)

Distance

Length of the hole (in yards)

Par

Par for the hole

Score

Actual number of stokes needed in this round

Details

Data come from a scorecard for one round of golf at the Potsdam Country Club. Par is the expected number of strokes a good golfer should need to complete the hole.

Source

Personal file

Groundhog Day

Description

Yearly data on US March temperature and Puxsutawney Phil's forecast on Groundhog Day

Format

A data frame with 122 observations on the following 3 variables.

Year

Year (1903-2025)

Shadow

Phil saw his shadow? (Yes or No)

USMarchTemp

Average US temperature in March of that year

Details

Every February 2nd (Groundhog Day) people gather at Gobbler's Knob in Puxsutawney, Pennsylvannia to see if an emerging groundhog (Phil) casts a shadow. Legend has it that a shadow fortells six more weks of winter, but no shadow indicates an early coming of spring. This dataset shows the outcome of Phil's shadow viewing for each year from 1903 to 2025, along with the average temerature in the US that March. One might expect six more week's of winter would mean colder temperatures in March.

Source

Data through 2016 from https://www.kaggle.com/datasets/groundhogclub/groundhog-day (May 2025).\

More recent years from https://www.groundhog.org/ and https://www.ncei.noaa.gov/.

Happy Planet Index

Description

Measurements related to happiness and well-being for 147 countries.

Format

A dataset with 147 observations on the following 9 variables.

Details

Data for 147 countries from the Happy Planet Index Project that works to quantify indicators of happiness, well-being, and ecological footprint at a country level.
** Updated for 4e (earlier version is now HappyPlanetIndex2010) **

Source

Abdallah, S. & Hoffman, A. (2024) The Happy Planet Index 2024 Data File.
Accessed from https://happyplanetindex.org/ March 2025

Happy Planet Index 2010

Description

Measurements related to happiness and well-being for 143 countries.

Format

A dataset with 143 observations on the following 11 variables.

Details

Data for 143 countries from the Happy Planet Index Project that works to quantify indicators of happiness, well-being, and ecological footprint at a country level.

Source

Marks, N., "The Happy Planet Index", www.TED.com/talks, August 29, 2010.
Data downloaded from http://www.happyplanetindex.org/data/

Heat and Cognition

Description

Effect of heat on cognitive ability

Format

A data frame with 46 observations on the following 3 variables.

AC

Whether the student had air conditioning on in the room, No or Yes

MathZRT

Z-score of reaction time solving math problems

ColorsZRT

Z-score of reaction time solving STROOP color problems

Details

Forty-six college students were asked to solve cognitive problems first thing in the morning during a heat wave in their Northeastern city. Twenty of the students had air-conditioning in their rooms and twenty-six did not. Z-scores of reaction times are given for math problems and for color dissonance problems.

Source

Cedeo Laurent JG, Williams A, Oulhote Y, Zanobetti A, Allen JG, Spengler JD "Reduced cognitive function during a heat wave among residents of non-air-conditioned buildings: An observational study of young adults in the summer of 2016." PLoS Med 15(7): e1002605, July 10, 2018. https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1002605. (Dataset is simplified from the repeated measures design used in the original study.)

Height Data

Description

Heights measured for the same 94 children over 18 years.

Format

A dataset with 94 observations on the following 33 variables.

Details

In the 1940's and 1950's, the heights of 39 boys and 54 girls, in centimeters, were measured at 30 different time points between the ages of 1 and 18 years as part of the University of California Berkeley growth study. Ages for measurement are 1, 1,25, 1,5, 1,75, 2, 3, 4, 5, 6, 7, 8, 8.5, 9, 9.5, 10, 10.5, 11, 11,5, 12, 12.5, 13, 13.5, 14, 14.5, 15, 15.5, 16, 16.5, 17, 17.5, 18.

Source

Tuddenham, R. D., and Snyder, M. M. (1954) "Physical growth of California boys and girls from birth to age 18", University of California Publications in Child Development, 1, 183-364.

Hockey Penalties - 2011

Description

Penalty minutes (per game) for NHL teams in 2010-11

Format

A dataset with 30 observations on the following 2 variables.

Details

Data give the average number of penalty minutes for each of the 30 National Hockey League (NHL) teams during the 2010-11 regular season.
** From 2e - dataset has been updated for 3e **

Source

Data obtained online at www.nhl.com

Hockey Penalties (2019)

Description

Penalty minutes (per game) for NHL teams in 2018-2019

Format

A data frame with 30 observations on the following 4 variables.

Team

Name of the team

PIM

Average penalty minutes per game

OppPIM

Average opponent's penalty minutes per game

Playoff

Did the team make the playoffs? (N or Y)

Details

Data give the average number of penalty minutes for each of the 30 National Hockey League (NHL) teams (and their opponents) during the 2018-2019 regular season.
** Updated for 3e (earlier version from 2010-11 is at HockeyPenalties2011). **

Source

Data obtained online at https://www.hockey-reference.com/leagues/NHL_2019.html#all_stats

Hockey Penalties (2025)

Description

Penalty minutes (per game) for NHL teams in 2024-2025

Format

A data frame with 32 observations on the following 10 variables.

Team

Name of the team

W

Wins

L

Losses

OL

Losses in overtime

PTS

Points = 2 x W + OL

GF

Goals scored

GA

Goals allowed

PIM

Average penalty minutes per game

OppPIM

Average opponent's penalty minutes per game

Playoff

Did the team make the playoffs? (N or Y)

Details

Data give the standings and average number of penalty minutes for each of the 30 National Hockey League (NHL) teams (and their opponents) during the 2024-2025 regular season.
** Updated for 4e (earlier versions are HockeyPenalties2019 and HockeyPenalties2011). **

Source

Data obtained online at https://www.hockey-reference.com/leagues/NHL_2025.html#all_stats

Hollywood Movies - 2019 to 2023

Description

Data on movies released in Hollywood between 2019 and 2023

Format

A data frame with 844 observations on the following 18 variables.

Movie

Title of the movie

Distributor

Primary U.S. distributor of the movie

Genre

Action Adventure, Black Comedy, Comedy, Concert/Performance, Documentary, Drama, Horror, Musical, Romantic Comedy, Thriller/Suspense, Western

RottenTomatoes

Rotten Tomatoes rating (critics)

AudienceScore

Audience rating (via Rotten Tomatoes)

RunTime

Running itme (in minutes)

Rating

G, PG, PG-13, or R

DomesticBO

Box office income for domestic (U.S.) viewers (in millions)

ForeignBO

Box office income for foreign viewers (in millions)

WorldwideBO

Box office income for all viewers (in millions)

OpenBO

Opening weekend box office income (in millions)

TheatersOpen

Number of screens for opening weekend

BOAvgOpen

Average box office income per theater, opening weekend

Budget

Production budget (in millions)

Profitability

WorldBO as a percentage of Budget

OpenProfit

Percentage of budget recovered on opening weekend

Country

Locations of production companies

Year

Year the movie was released

Details

Information from 844 movies released from Hollywood (or elswhere in the US) between 2019 and 2023 that had at least $100,000 in box office income as of February 2025.
** Updated for 4e (earlier versions are HollywoodMovies2018, HollywoodMovies2013, and HollywoodMovies2011). **

Source

Movie data obtained in February 2025 from
https://www.the-numbers.com/
https://www.rottentomatoes.com/

Hollywood Movies in 2011

Description

Data on movies released in Hollywood in 2011

Format

A dataset with 136 observations on the following 14 variables.

Details

Information from 136 movies released from Hollywood in 2011.
** This dataset has been updated for 2e with more years of data (in HollywoodMovies) **

Source

McCandless, D., "Most Profitable Hollywood Movies" from "Information is Beautiful" at
http://www.informationisbeautiful,net.data/ and
http://bit.ly/hollywoodbudgets.

Hollywood Movies - 2013

Description

Data on movies released in Hollywood between 2007 and 2013

Format

A dataset with 970 observations on the following 16 variables.

Details

Information from 970 movies released from Hollywood between 2007 and 2013.
** From 2e - dataset has been updated for 3e **

Source

McCandless, D., "Most Profitable Hollywood Movies" from "Information is Beautiful" at
http://www.informationisbeautiful,net.data/ and
http://bit.ly/hollywoodbudgets.

Hollywood Movies - 2012 to 2018

Description

Data on movies released in Hollywood between 2012 and 2018

Format

A data frame with 1295 observations on the following 15 variables.

Movie

Title of the movie

LeadStudio

Primary U.S. distributor of the movie

RottenTomatoes

Rotten Tomatoes rating (critics)

AudienceScore

Audience rating (via Rotten Tomatoes)

Genre

One of Action Adventure, Black Comedy, Comedy, Concert, Documentary, Drama, Horror, Musical, Romantic Comedy, Thriller, or Western

TheatersOpenWeek

Number of screens for opening weekend

OpeningWeekend

Opening weekend gross (in millions)

BOAvgOpenWeekend

Average box office income per theater, opening weekend

Budget

Production budget (in millions)

DomesticGross

Gross income for domestic (U.S.) viewers (in millions)

WorldGross

Gross income for all viewers (in millions)

ForeignGross

Gross income for foreign viewers (in millions)

Profitability

WorldGross as a percentage of Budget

OpenProfit

Percentage of budget recovered on opening weekend

Year

Year the movie was released

Details

Information from 1295 movies released from Hollywood between 2012 and 2018.
** Updated for 3e (earlier versions are HollywoodMovies2013 and HollywoodMovies2011). **

Source

Movie data obtained from
https://www.boxofficemojo.com/
https://www.the-numbers.com/
https://www.rottentomatoes.com/

Homes For Sale (2025)

Description

Data on homes sold in four states in 2025

Format

A data frame with 120 observations on the following 6 variables.

State

Location of the home (NY, IA, CA, or FL)

Price

Asking price (in $1,000's)

Size

Area of all rooms (in sq. ft.)

Beds

Number of bedrooms

Baths

Number of bathrooms

Zip

Zip code for the home

Details

Data for samples of 30 homes recently sold in each state, selected from random zip codes at zillow.com.
** Updated for 4e (earlier versions are HomesForSale3e (2019) and HomesForSale2e (2010)). **

Source

Data collected from https://www.zillow.com/ in March 2025.

Home for Sale - 2e

Description

Data on homes for sale in four states

Format

A dataset with 120 observations on the following 5 variables.

Details

Data for samples of homes for sale in each state, selected from zillow.com.
** From 2e - dataset has been updated for 3e **

Source

Data collected from www.zillow.com in 2010.

Homes For Sale (2019)

Description

Data on homes for sale in four states in 2019

Format

A data frame with 120 observations on the following 5 variables.

State

Location of the home (CA, NJ, NY, or PA)

Price

Asking price (in $1,000's)

Size

Area of all rooms (in 1,000's sq. ft.)

Beds

Number of bedrooms

Baths

Number of bathrooms

Details

Data for samples of homes for sale in each state, selected from zillow.com.
** Updated for 3e (earlier version from 2010 is in HomesForSale2e). **

Source

Data collected from https://www.zillow.com/ in 2019.

Homes For Sale in California (2025)

Description

Data for a sample of homes sold in California

Format

A data frame with 30 observations on the following 6 variables.

State

Location of the home (CA)

Price

Asking price (in $1,000's)

Size

Area of all rooms (in sq. ft.)

Beds

Number of bedrooms

Baths

Number of bathrooms

Zip

Zip code for the home

Details

Data for a sample of 30 homes recently sold in California, selected from random zip codes at zillow.com. This is a subset of the HomesForSale dataset.
** Updated for 4e (earlier versions are HomesForSaleCA3e (2019) and HomesForSaleCA2e (2010)). **

Source

Data collected from https://www.zillow.com/ in March 2025.

Home for Sale in California (2010)

Description

Data for a sample of homes offered for sale in California

Format

A dataset with 30 observations on the following 5 variables.

Details

Data for samples of homes for sale in California, selected from zillow.com.
** From 2e - dataset has been updated for 3e **

Source

Data collected from www.zillow.com in 2010.

Homes For Sale in California (2019)

Description

Data for a sample of homes offered for sale in California

Format

A data frame with 30 observations on the following 5 variables.

State

Location of the home (CA)

Price

Asking price (in $1,000's)

Size

Area of all rooms (in 1,000's sq. ft.)

Beds

Number of bedrooms

Baths

Number of bathrooms

Details

Data fora sample of homes for sale in California, selected from zillow.com. This is a subset of the HomesForSale dataset.
** Updated for 3e (earlier version from 2010 is in HomesForSaleCA2e). **

Source

Data collected from https://www.zillow.com/ in 2019.

Homes For Sale in Canton, NY (2025)

Description

Data for a sample of homes sold in Canton, NY in 2025

Format

A data frame with 10 observations on the following 4 variables.

Price

Asking price (in $1,000's)

Size

Area of all rooms (in sq. ft.)

Beds

Number of bedrooms

Baths

Number of bathrooms

Details

Data for a sample of homes recently sold in Canton, NY, selected from zillow.com.
** Updated for 4e (earlier versions are HomesForSaleCanton3e (2019) and HomesForSaleCanton2e (2010)). **

Source

Data collected from https://www.zillow.com/ in March 2025.

Homes for sale in Canton, NY (2010)

Description

Prices of homes for sale in Canton, NY

Format

A dataset with 10 observations on the following variable.

Details

Data for samples of homes for sale in Canton, NY, selected from zillow.com.
** From 2e - dataset has been updated for 3e **

Source

Data collected from www.zillow.com in 2010.

Homes For Sale in Canton, NY (2019)

Description

Data for a sample of homes offered for sale in Canton, NY

Format

A data frame with 10 observations on the following 4 variables.

Price

Asking price (in $1,000's)

Size

Area of all rooms (in 1,000's sq. ft.)

Beds

Number of bedrooms

Baths

Number of bathrooms

Details

Data for a sample of homes for sale in Canton, NY, selected from zillow.com.
** Updated for 3e (earlier version from 2010 is in HomesForSaleCanton2e). **

Source

Data collected from https://www.zillow.com/ in 2019.

Homes For Sale in New York (2025)

Description

Data for a sample of homes sold in New York (state)

Format

A data frame with 30 observations on the following 6 variables.

State

Location of the home (NY)

Price

Asking price (in $1,000's)

Size

Area of all rooms (in sq. ft.)

Beds

Number of bedrooms

Baths

Number of bathrooms

Zip

Zip code for the home

Details

Data for a sample of 30 homes recently sold in New York, selected from random zip codes at zillow.com. This is a subset of the HomesForSale dataset.
** Updated for 4e (earlier versions are HomesForSaleNY3e (2019) and HomesForSaleNY2e (2010)). **

Source

Data collected from https://www.zillow.com/ in 2025.

Home for Sale in New York - 2e

Description

Data for a sample of homes offered for sale in New York State

Format

A dataset with 30 observations on the following 5 variables.

Details

Data for samples of homes for sale in New York, selected from zillow.com.
** From 2e - dataset has been updated for 3e **

Source

Data collected from www.zillow.com in 2010.

Homes For Sale in New York (2019)

Description

Data for a sample of homes offered for sale in New York (state)

Format

A data frame with 30 observations on the following 5 variables.

State

Location of the home (NY)

Price

Asking price (in $1,000's)

Size

Area of all rooms (in 1,000's sq. ft.)

Beds

Number of bedrooms

Baths

Number of bathrooms

Details

Data for a sample of homes for sale in New York, selected from zillow.com. This is a subset of the HomesForSale dataset.
** Updated for 3e (earlier version from 2010 is in HomesForSaleNY2e). **

Source

Data collected from https://www.zillow.com/ in 2019.

Homing Pigeons

Description

Results from the 2019 Midwest Classic Homing Pigeon race

Format

A data frame with 1412 observations on the following 5 variables.

Position

Finishing position in the race

Loft

Name of the pigeon's home loft

Sex

C=cock (male) or H=hen (female)

Distance

Distance (in miles) from release point to home loft

Speed

Speed (in yards per minute)

Details

Finishing results from 1412 pigeons completing the 2019 Midwest Classic race for homing pigeons on June 30, 2019. Each loft may enter multiple pigeons.

Source

Final race report from the Midwest Homing Pigeon Association, downloaded from http://www.midwesthpa.com/MIDFinalReports.htm

Honeybee Colonies - 2012

Description

Number of honeybee colonies (1995-2012)

Format

A dataset with 18 observations on the following 2 variables.

Details

Data collected from the USDA on the estimated number of honeybee colonies in the US for the years 1995 through 2012.

Source

USDA National Agriculture and Statistical Services,
http://usda.mannlib.cornell.edu/MannUsda/viewDocumentInfo.do?documentID=1191 Accessed September 2015.

Honeybee Colonies - 2023

Description

Number of honeybee colonies (2008-2023)

Format

A dataset with 16 observations on the following 2 variables.

Details

Data collected from the USDA on the estimated number of honeybee colonies in the US for the years 2008 through 2023. Updated for 4e (earlier version is now Honeybee2012 with data from 1995-2012).

Source

USDA National Agriculture and Statistical Services, https://quickstats.nass.usda.gov/ (Accessed February 2025)

Honeybee Circuits

Description

Number of circuits for honeybee dances and nest quality

Format

A dataset with 78 observations on the following 2 variables.

Details

When honeybees are looking for a new home, they send out scouts to explore options. When a scout returns, she does a "waggle dance" with multiple circuit repetitions to tell the swarm about the option she found. The bees then decide between the options and pick the best one. Scientists wanted to find out how honeybees decide which is the best option, so they took a swarm of honeybees to an island with only two possible options for new homes: one of very high honeybee quality and one of low quality. They then kept track of the scouts who visited each option and counted the number of waggle dance circuits each scout bee did when describing the option.

Source

Seeley, T., Honeybee Democracy, Princeton University Press, Princeton, NJ, 2010, p. 128

Honeybee Waggle

Description

Honeybee dance duration and distance to nesting site

Format

A dataset with 7 observations on the following 2 variables.

Details

When honeybee scouts find a food source or a nice site for a new home, they communicate the location to the rest of the swarm by doing a "waggle dance." They point in the direction of the site and dance longer for sites farther away. The rest of the bees use the duration of the dance to predict distance to the site.

Source

Seeley, T., Honeybee Democracy, Princeton University Press, Princeton, NJ, 2010, p. 128

Hot Dog Eating Contest

Description

Winning number of hot dogs consumed in an eating contest

Format

A dataset with 10 observations on the following 2 variables.

Details

Every Fourth of July, Nathan's Famous in New York City holds a hot dog eating contest, in which contestants try to eat as many hot dogs (with buns) as possible in ten minutes. The winning number of hot dogs are given for each year from 2002-2011.
** From 1e - dataset has been updated for 2e **

Source

Downloaded from https://en.wikipedia.org/wiki/Nathan's_Hot_Dog_Eating_Contest

Hot Dog Eating Contest - 2015

Description

Winning number of hot dogs consumed in an eating contest

Format

A dataset with 14 observations on the following 2 variables.

Details

Every Fourth of July, Nathan's Famous in New York City holds a hot dog eating contest, in which contestants try to eat as many hot dogs (with buns) as possible in ten minutes. The winning number of hot dogs are given for each year from 2002-2015.
** From 2e - dataset has been updated for 3e **

Source

Downloaded from https://en.wikipedia.org/wiki/Nathan's_Hot_Dog_Eating_Contest

Hot Dog Eating Contest - 2019

Description

Winning number of hot dogs consumed in an eating contest (2002-2019)

Format

A data frame with 18 observations on the following 2 variables.

Year

Year of the contest: 2002 to 2019

HotDogs

Winning number of hot dogs consumed

Details

Every Fourth of July, Nathan's Famous in New York City holds a hot dog eating contest, in which contestants try to eat as many hot dogs (with buns) as possible in ten minutes. The winning number of hot dogs are given for each year from 2002-2019.
** Data set updated for 3e (earlier versions are HotDogs2015 and HotDogs1e) **

Source

Downloaded from https://en.wikipedia.org/wiki/Nathan's_Hot_Dog_Eating_Contest

Hot Dog Eating Contest - 2024

Description

Winning number of hot dogs consumed in an eating contest (2002-2024)

Format

A data frame with 23 observations on the following 2 variables.

Year

Year of the contest: 2002 to 2024

HotDogs

Winning number of hot dogs consumed

Details

Every Fourth of July, Nathan's Famous in New York City holds a hot dog eating contest, in which contestants try to eat as many hot dogs (with buns) as possible in ten minutes. The winning number of hot dogs are given for each year from 2002-2024.
** Data set updated for 4e (earlier versions are HotDogs2019, HotDogs2015, and HotDogs1e) **

Source

Downloaded from https://en.wikipedia.org/wiki/Nathan's_Hot_Dog_Eating_Contest

Housing Starts - 2015

Description

Quarterly housing starts in the United States from 2000-2015

Format

A dataset with 64 observations on the following 3 variables.

Details

Number of new homes started in the US for each quarter from 2000-2015.
** From 2e - dataset has been updated for 3e **

Source

Census.gov website https://www.census.gov/econ/currentdata/
https://www.census.gov/econ/currentdata/dbsearch?program=RESCONST&startYear=2000 &endYear=2016&categories=STARTS&dataType=SINGLE&geoLevel=US&notAdjusted=1&submit=GET+DATA&releaseScheduleId=

Housing Starts (2000-2018)

Description

Quarterly housing starts in the United States from 2000-2018

Format

A data frame with 76 observations on the following 3 variables.

Year

Year (2000 to 2018)

Quarter

Q1=Jan-Mar, Q2=Apr-June, Q3=July-Sept, Q4=Oct-Dec

Houses

New US residential house construction starts (in thousands)

Details

Number of new homes started in the US for each quarter from 2000-2018.
Updated for 3e (earlier version is in HouseStarts2015)

Source

Census.gov website https://www.census.gov/econ/currentdata/

https://www.census.gov/econ/currentdata/dbsearch?program=RESCONST&startYear=2000&endYear=2018&categories=STARTS&dataType=SINGLE&geoLevel=US&notAdjusted=1&submit=GET+DATA&releaseScheduleId=

Housing Starts (2000-2024)

Description

Quarterly housing starts in the United States from 2000-2024

Format

A data frame with 100 observations on the following 3 variables.

Year

Year (2000 to 2024)

Quarter

Q1=Jan-Mar, Q2=Apr-June, Q3=July-Sept, Q4=Oct-Dec

Houses

New US residential house construction starts (in thousands)

Details

Number of new homes started in the US for each quarter from 2000-2024.
Updated for 4e (earlier version are in HouseStarts2018 and HouseStarts2015)

Source

Census.gov website https://www.census.gov/econ/currentdata/

https://www.census.gov/econ/currentdata/dbsearch?program=RESCONST&startYear=2000&endYear=2024&categories=STARTS&dataType=SINGLE&geoLevel=US&notAdjusted=1&submit=GET+DATA&releaseScheduleId=

Human Tears -Sadness and Sexual Arousal

Description

Differences in sadness and sexual arousal ratings for 25 men sniffing female tears or a placebo in a matched pairs experiment.

Format

A data frame with 25 observations on the following 2 variables.

SexDiff

Difference in sexual arousal rating (placebo rating - tears rating)

SadDiff

Difference in sadness rating (placebo rating - tears rating)

Details

Twenty-five men had a pad attached to their upper lip that contained either female tears collected from women who watched a sad film or a salt solution (as a placebo) that had been trickled down the same women's faces. The data were collected following a double-blind matched pairs design, where the order was randomized. The men were shown pictures of female faces and asked "To what extent is this face sad?" or "To what extent is this face sexually arousing?" Men's answers were input using a Visual Analog Scale, which were then converted to a scale with results between about 200 and 800. The data show the difference in rating (placebo rating minus sadness rating) for each man for the sad question (SadDiff) or the sexual arousal question (SexDiff). .Data are approximated from information given in the article.

Source

Gelstein, S, et al., "Human Tears Contain a Chemosignal," Science, 331(6014), 226-230, January 14, 2011.

Human Tears - Testosterone

Description

Differences in testosterone levels for 50 men in a matched pairs experiment, where the differences are between sniffing female tears and sniffing a placebo

Format

A data frame with 50 observations on the following 3 variables.

Placebo

Testosterone level after sniffing a placebo

Tears

Testosterone level after sniffing female tears

Difference

Difference in testosterone level (Placebo - Tears)

Details

Fifty men had a pad attached to their upper lip that contained either female tears collected from women who watched a sad film or a salt solution (as a placebo) that had been trickled down the same women's faces. The data were collected following a double-blind matched pairs design, where the order was randomized and the data were collected on consecutive days. After sniffing each substance (placebo or tears), men had their salivary testosterone levels measured, in pg/ml. Data are approximated from information given in the article.

Source

Gelstein, S, et al., "Human Tears Contain a Chemosignal," Science, 331(6014), 226-230, January 14, 2011.

Hurricanes - 2014

Description

Hurricanes making landfall on the US east coast each year (1914-2014)

Format

A dataset with 64 observations on the following 3 variables.

Details

Number of hurricanes making landfall on the East coast of the United States - yearly 1914-2014.
** From 2e - dataset has been updated for 3e **

Source

Weather Underground website at https://www.wunderground.com/hurricane/hurrarchive.asp

Hurricanes (1914 to 2018)

Description

Hurricanes in the North Atlantic each year (1914-2018)

Format

A data frame with 105 observations on the following 2 variables.

Year

Year (1914 to 2018)

Hurricanes

Number of North Atlantic hurricanes

Details

Number of North Atlantic hurricanes - yearly 1914-2018.
** Updated for 3e (earlier version through 2014 is in Hurricanes2014). **

Source

Weather Underground website at https://www.wunderground.com/hurricane/archive

Hurricanes (1914 to 2024)

Description

Hurricanes in the North Atlantic each year (1914-2024)

Format

A data frame with 111 observations on the following 2 variables.

Year

Year (1914 to 2024)

Hurricanes

Number of North Atlantic hurricanes

Details

Number of North Atlantic hurricanes - yearly 1914-2024.
** Updated for 4e (earlier versions are in Hurricanes2018 and Hurricanes2014). **

Source

Weather Underground website at https://www.wunderground.com/hurricane/archive

Intensive Care Unit Admissions

Description

Data from patients admitted to an intensive care unit

Format

A dataset with 200 observations on the following 21 variables.

Details

Data from a sample of 200 patients following admission to an adult intensive care unit (ICU).

Source

DASL dataset downloaded from http://lib.stat.cmu.edu/DASL/Datafiles/ICU.html

Immune Tea

Description

Interferon gamma production and tea drinking

Format

A dataset with 21 observations on the following 2 variables.

Details

Eleven healthy non-tea-drinking individuals were asked to drink five or six cups of tea a day, while ten healthy non-tea and non-coffee-drinkers were asked to drink the same amount of coffee, which has caffeine but not the L-theanine that is in tea. The groups were randomly assigned. After two weeks, blood samples were exposed to an antigen and production of interferon gamma was measured.

Source

Adapted from Kamath, et.al., "Antigens in tea-Beverage prime human V 2V2 T cells in vitro and in vivo for memory and non-memory antibacterial cytokine responses", Proceedings of the National Academy of Sciences, May 13, 2003.

Inkjet Printers

Description

Data from online reviews of inkjet printers (2025)

Format

A dataset with 25 observations on the following 7 variables.

Details

Information from reviews of all-one inkjet printers at Rtings.com in January 2025.

Source

Inkjet printer data found at https://www.rtings.com/printer/tools/table/157814, January 2025.

Inkjet Printers - 1e

Description

Data from online reviews of inkjet printers(2011)

Format

A dataset with 20 observations on the following 6 variables.

Details

Information from reviews of inkjet printers at PCMag.com in August 2011.

Source

Inkjet printer reviews found at http://www.pcmag.com/reviews/printers, August 2011.

Life Expectancy and Vehicle Registrations (2022)

Description

Yearly US life expectancy and number of registered vehicles (1970-2022)

Format

A data frame with 53 observations on the following 3 variables.

Year

Year (1970 to 2022)

LifeExpectancy

Average life expectancy (in years) for babies born in the year

Vehicles

Number of motor vehicles registered in the US (in millions)

Details

Life expectancy (in years for babies born each year) and number of vehicles registered in the US for each year from 1970 to 2022.
** Updated for 4e (earlier versions are LifeExpectancyVehicles2e, LifeExpectancyVehicles2e, and LifeExpectancyVehicles1e) **

Source

Vehicle registrations from the Federal Highway Administration, https://www.fhwa.dot.gov/policyinformation/statistics.cfm.

Lifetime data from the Centers for Disease Control and Prevention, National Center for Health Statistics https://www.cdc.gov/nchs/fastats/life-expectancy.htm.

Life Expectancy and Vehicle Registrations - 1e

Description

Yearly US life expectancy and number of registered vehicles (1970-2009)

Format

A dataset with 40 observations on the following 3 variables.

Details

Life expectancy (in years for babies born each year) and number of vehicles registered in the US for each year from 1970 to 2009.
** From 1e - dataset has been updated for 2e **

Source

Vehicle registrations from US Census Bureau, http://www.census.gov/compendia/statab/cats/transportation.html Lifetime data from the Centers for Disease Control and Prevention, National Center for Health Statistics, Health Data Interactive, www.cdc.gov/nchs/hdi.htm

Life Expectancy and Vehicle Registrations - 2e

Description

Yearly US life expectancy and number of registered vehicles (1970-2013)

Format

A dataset with 44 observations on the following 3 variables.

Details

Life expectancy (in years for babies born each year) and number of vehicles registered in the US for each year from 1970 to 2013.
** From 2e - dataset has been updated for 3e **

Source

Vehicle registrations from US Census Bureau, http://www.census.gov/compendia/statab/cats/transportation.html Lifetime data from the Centers for Disease Control and Prevention, National Center for Health Statistics, Health Data Interactive, www.cdc.gov/nchs/hdi.htm

Life Expectancy and Vehicle Registrations (2017)

Description

Yearly US life expectancy and number of registered vehicles (1970-2017)

Format

A data frame with 48 observations on the following 3 variables.

Year

Year (1970 to 2017)

LifeExpectancy

Average life expectancy (in years) for babies born in the year

Vehicles

Number of motor vehicles registered in the US (in millions)

Details

Life expectancy (in years for babies born each year) and number of vehicles registered in the US for each year from 1970 to 2017.
** Updated for 3e (earlier versions are LifeExpectancyVehicles2e and LifeExpectancyVehicles1e) **

Source

Vehicle registrations from the Federal Highway Administration, https://www.fhwa.dot.gov/policyinformation/statistics.cfm.

Lifetime data from the Centers for Disease Control and Prevention, National Center for Health Statistics https://www.cdc.gov/nchs/hus/contents2019.htm?search=Life_expectancy,.

Light at Night for Mice

Description

Data on body mass gain from an experiment with mice having different nighttime light conditions

Format

A dataset with 18 observations on the following 2 variables.

Details

In this study, 18 mice were randomly split into two groups. One group was on a normal light/dark cycle (Dark) and the other group had light during the day and dim light at night (Light). The dim light was equivalent to having a television set on in a room. The mice in darkness ate most of their food during their active (nighttime) period, matching the behavior of mice in the wild. The mice with dim light at night, however, consumed much of their food during the well-lit rest period, when most mice are usually sleeping. The change in body mass was recorded after three weeks.
** See also LightatNight4Weeks or LightatNight8Weeks for more variables measured at other points in the same experiment, with a third experimental condition which had 9 additional mice with a bright light on all the time. **

Source

Fonken, L., et. al., "Light at night increases body mass by shifting time of food intake," Proceedings of the National Academy of Sciences, October 26, 2010; 107(43): 18664-18669.

Light at Night for Mice - After 4 Weeks

Description

Data from an experiment with mice having different nighttime light conditions

Format

A dataset with 27 observations on the following 9 variables.

Details

In this study, 27 mice were randomly split into three groups. One group was on a normal light/dark cycle (LD), one group had bright light on all the time (LL), and one group had light during the day and dim light at night (DM). The dim light was equivalent to having a television set on in a room. The mice in darkness ate most of their food during their active (nighttime) period, matching the behavior of mice in the wild. The mice in both dim light and bright light, however, consumed more than half of their food during the well-lit rest period, when most mice are sleeping. Values in this dataset are recorded after four weeks in the experimental condition.
** This dataset was named LightatNight in the first edition **
** See also LightatNight8Weeks for the same data after 8 weeks or LightatNight with just BMGain after 3 weeks for the DM and LD groups. **

Source

Fonken, L., et. al., "Light at night increases body mass by shifting time of food intake," Proceedings of the National Academy of Sciences, October 26, 2010; 107(43): 18664-18669.

Light at Night for Mice - After 8 Weeks

Description

Data from an experiment with mice having different nighttime light conditions

Format

A dataset with 27 observations on the following 9 variables.

Details

In this study, 27 mice were randomly split into three groups. One group was on a normal light/dark cycle (LD), one group had bright light on all the time (LL), and one group had light during the day and dim light at night (DM). The dim light was equivalent to having a television set on in a room. The mice in darkness ate most of their food during their active (nighttime) period, matching the behavior of mice in the wild. The mice in both dim light and bright light, however, consumed more than half of their food during the well-lit rest period, when most mice are sleeping. Values in this dataset are recorded after eight weeks in the experimental condition.
** See also LightatNight4Weeks for the same data after 4 weeks or LightatNight with just BMGain after 3 weeks for just the DM and LD groups. **

Source

Fonken, L., et. al., "Light at night increases body mass by shifting time of food intake," Proceedings of the National Academy of Sciences, October 26, 2010; 107(43): 18664-18669.

Malevolent Uniforms NFL

Description

Perceived malevolence of uniforms and penalties for National Football League (NFL) teams

Format

A dataset with 28 observations on the following 3 variables.

Details

Participants with no knowledge of the teams rated the jerseys on characteristics such as timid/aggressive, nice/mean and good/bad. The averages of these responses produced a "malevolence" index with higher scores signifying impressions of more malevolent uniforms. To measure aggressiveness, the authors used the amount of penalty yards converted to z-scores and averaged for each team over the seasons from 1970-1986.

Source

Frank and Gilovich, "The Dark Side of Self- and Social Perception: Black Uniforms and Aggression in Professional Sports", Journal of Personality and Social Psychology, Vol. 54, No. 1, 1988, p. 74-85.

Malevolent Uniforms NHL

Description

Perceived malevolence of uniforms and penalties for National Hockey League (NHL) teams

Format

A dataset with 28 observations on the following 3 variables.

Details

Participants with no knowledge of the teams rated the jerseys on characteristics such as timid/aggressive, nice/mean and good/bad. The averages of these responses produced a "malevolence" index with higher scores signifying impressions of more malevolent uniforms. To measure aggressiveness, the authors used the amount of penalty minutes converted to z-scores and averaged for each team over the seasons from 1970-1986.

Source

Frank and Gilovich, "The Dark Side of Self- and Social Perception: Black Uniforms and Aggression in Professional Sports", Journal of Personality and Social Psychology, Vol. 54, No. 1, 1988, p. 74-85.

Mammal Longevity

Description

Longevity and gestation period for mammals

Format

A dataset with 40 observations on the following 3 variables.

Details

Dataset with average lifespan (in years) and typical gestation period (in days) for 40 different species of mammals.

Source

2010 World Almanac, pg. 292.

Manhattan Apartment Prices (2025)

Description

Apartment prices for sale in Manhattan in 2025

Format

A data frame with 20 observations on the following variable.

Rent

Monthly rent (in dollars)

Details

Monthly rents for a sample of 20 one-bedroom apartments in Manhattan, NY in March 2025

Source

Apartments newly available on Zillow at https://www.zillow.com/manhattan-new-york-ny/rentals/, March, 2025.

Manhattan Apartment Prices - 2011

Description

Monthly rent for one-bedroom apartments in Manhattan, NY

Format

A dataset with 20 observations on the following variable.

Details

Monthly rents for a sample of 20 one-bedroom apartments in Manhattan, NY that were advertised on Craig's List in July, 2011.
** From 2e - dataset has been updated for 3e **

Source

Apartments advertised on Craig's List at newyork.craigslist.org, July 5, 2011.

Manhattan Apartment Prices (2019)

Description

Apartment prices for sale in Manhattan in 2019

Format

A data frame with 20 observations on the following variable.

Rent

Monthly rent (in dollars)

Details

Monthly rents for a sample of 20 one-bedroom apartments in Manhattan, NY that were advertised on Craig's List in November, 2019.

Source

Apartments newly advertised on Craig's List at https://newyork.craigslist.org/, November, 2019.

Marriage Ages

Description

Ages for husbands and wives from marriage licenses

Format

A dataset with 100 observations on the following 2 variables.

Details

Data from a sample of 100 marriage licenses in St. Lawrence County, NY gives the ages of husbands and wives for newly married couples.

Source

Thanks to Linda Casserly, St. Lawrence County Clerk's Office

Masters Golf Scores

Description

Scores from the 2011 Masters golf tournament

Format

A dataset with 20 observations on the following 2 variables.

Details

Data for a random sample of 20 golfers who made the cut at the 2011 Masters golf tournament.

Source

2011 Masters tournament results at http://www.masters.com/en_US/discover/past_winners.html

Fruitfly Survival - by Mate Choice

Description

Number of fruitflies surviving depending on number of mating choices.

Format

A dataset with 50 observations on the following 3 variables.

Details

In an experiment, two hundred larvae from female fruitflies that were exposed to many male fruitflies were tracked to see how many survived. This was compared to a different set of 200 larvae from females that were exposed to only one male each. Values in the dataset give how many of the 200 larvae survived. This process was replicated 50 times, so each row of the dataset corresponds to the survival counts (and difference) for one run, starting with 200 larvae of each type.

Source

Patridge, L. (1980). "Mate choice increases a component of offspring fitness in fruit flies," Nature, 283:290-291, 1/17/80.

Mental Muscle

Description

Comparing actual movements to mental imaging movements

Format

A dataset with 32 observations on the following 3 variables.

Details

In this study, participants were asked to either perform actual arm pointing motions or to mentally imagine equivalent arm pointing motions. Participants then developed muscle fatigue by holding a heavy weight out horizontally as long as they could. After becoming fatigued, they were asked to repeat the previous mental or actual motions. Eight participants were assigned to each group, and the time in seconds to complete the motions was measured before and after fatigue.

Source

Data approximated from summary statistics in: Demougeot L. and Papaxanthis C., "Muscle Fatigue Affects Mental Simulation of Action," The Journal of Neuroscience, July 20, 2011, 31(29):10712-10720.

Miami Heat Basketball

Description

Game log data for the Miami Heat basketball team in 2010-11

Format

A dataset with 82 observations on the following 33 variables.

Details

Information from online boxscores for all 82 regular season games payed by the Miami Heat basketball team during the 2010-11 season.
** This is from the first edition, updated in second edition to GSWarriors dataset **

Source

Data for the 2010-11 Miami games downloaded from
http://www.basketball-reference.com/teams/MIA/2011/gamelog/

Mindset Matters

Description

Data from a study of perceived exercise with maids

Format

A dataset with 75 observations on the following 14 variables.

Details

In 2007 a Harvard psychologist recruited 75 female maids working in different hotels to participate in a study. She informed 41 maids (randomly chosen) that the work they do satisfies the Surgeon General's recommendations for an active lifestyle (which is true), giving them examples for how and why their work is good exercise. The other 34 maids were told nothing (uninformed). Various characteristics (weight, body mass index, ...) were recorded for each subject at the start of the experiment and again four weeks later. Maids with missing values for weight change have been removed.

Source

Crum, A.J. and Langer, E.J. (2007). Mind-Set Matters: Exercise and the Placebo Effect, Psychological Science, 18:165-171. Thanks to the authors for supplying the data.

Mustang Prices

Description

Price, age, and mileage for used Mustang cars at an internet website (2025)

Format

A dataset with 30 observations on the following 3 variables.

Details

A statistics student was interested in prices for used Mustang cars being offered for sale on an internet site. He sampled 30 cars from the website and recorded the age (in years), mileage (in thousands of miles), and asking price (in $1,000's) for each car in his sample.
** Updated for 4e (earlier version is now MustangPrice1e). **

Source

Student project with data collected from autotrader.com in March, 2025.

Mustang Prices (2008)

Description

Price, age, and mileage for used Mustang cars at an internet website (2008)

Format

A dataset with 25 observations on the following 3 variables.