StatCrunch logo (home)

Data sets shared by StatCrunch members
Showing 1 to 15 of 1446 data sets matching age
Data Set/Description Owner Last edited Size Views
USA Car Accidents in 2011
This data set contains information for drivers involved in car accidents in the United States during 2011. The variables include the age in years of the person (Age), the gender of the person (Gender), the month in which the accident occurred (Month), and the day of the week of the accident (DayOfWeek).
statcrunch_featuredSep 12, 2017919KB1365
USA Car Accidents in 2011
This data set contains information for drivers involved in car accidents in the United States during 2011. The variables include the age in years of the person (Age), the gender of the person (Gender), the month in which the accident occurred (Month), and the day of the week of the accident (DayOfWeek).
bdodson94@su.eduOct 5, 2017919KB284
Shark Attacks Worldwide
This data comes from www.sharkattackfile.net. It records data on all shark attacks in recorded history including attacks before 1800. Included is all known information on the shark attack including the date, location, information on the individual who was attacked, details on the injuries sustained by the victim, and the species of the shark
statcrunch_featuredJun 28, 20171MB2704
Cereal Brands
Data on several variable of different brands of cereal. Number of cases: 77 Variable Names: Name: Name of cereal mfr: Manufacturer of cereal where A = American Home Food Products; G = General Mills; K = Kelloggs; N = Nabisco; P = Post; Q = Quaker Oats; R = Ralston Purina type: cold or hot calories: calories per serving protein: grams of protein fat: grams of fat sodium: milligrams of sodium fiber: grams of dietary fiber carbo: grams of complex carbohydrates sugars: grams of sugars potass: milligrams of potassium vitamins: vitamins and minerals - 0, 25, or 100, indicating the typical percentage of FDA recommended shelf: display shelf (1, 2, or 3, counting from the floor) weight: weight in ounces of one serving cups: number of cups in one serving rating: a rating of the cereals
statcrunch_featuredApr 3, 20174KB1121
US Workforce Participation
This data primarily comes from two sources: Federal Reserve Bank of St. Louis and the US Bureau of Labor Statistics .
ColumnDescription
YearThe calendar year for each value
Annual Average Workforce ParticipationDefined by the Bureau of Labor Statistics as "the percentage of the population [16 years and older] that is either employed or unemployed (that is, either working or actively seeking work). Note that 2015's Annual Average is calculated using the first 11 months."
Male Workforce Participation RateAnnual workforce participation rate for males.
Female Workforce Participation RateAnnual workforce participation rate for females.
Male Inactivity Rate Aged 25-54Defined as the proportion of the male population aged 25-54 that is not in the labour force. Common reasons for leaving labour force: college, retirement, stay at home, can't find work and no longer try.
Change in Rate (Male Inactivity Rate Aged 25-54)The change in the inactivity rate calculated as the current year minus the previous year.
Female Inactivity Rate Aged 25-54Defined as the proportion of the female population aged 25-54 that is not in the labour force.
Change in Rate (Female Inactivity Rate Aged 25-54)The change in the inactivity rate calculated as the current year minus the previous year.
Presidential ControlPolitical party of president.
Senate ControlPolitical party of the Senate majority
House ControlPolitical party of the House of Representatives majority.
Legislative Branch (House and Senate)Combined control of Senate and House of Representativs
statcrunch_featuredJun 27, 201710KB510
Titanic Survival Data
This has the survival data for the passengers on the Titanic. It also has if they were an adult or child, their gender, and the class they were staying on.
statcrunch_featuredApr 3, 201748KB623
2014 MLB Top 100 Batters
This data came from ESPN.com and has the top 100 batters by WAR (wins above replacement). AB: At bats R: Runs H: Hits 2B: Doubles 3B: Triples RBI: Runs batted in SB: Stolen Bases BB: Walks SO: Strikeouts AVG: Batting average OBP: On Base Percentage SLG: Slugging Percentage OPS: OBP + SLG WAR: Wins Above Replacement
statcrunch_featuredApr 3, 20179KB474
GunsAndGunDeathsByCountry
This data set contains data regarding gun ownership and gun deaths in various categories for 73 different countries. The data were obtained on 8/28/16 from Wikipedia. The Wikipedia pages have more information about the sources for the data values for each country and the dates on which the original data were collected. A. Variables obtained from https://en.wikipedia.org/wiki/Estimated_number_of_guns_per_capita_by_country Guns/100: total number of guns per 100 population B. Variables obtained from https://en.wikipedia.org/wiki/List_of_countries_by_firearm-related_death_rate The dates on which data was obtained for the various countries range from 1995 to 2016. Country: name of country Total gun deaths/100,000: total number of gun deaths in one year per 100,000 population (sum of gun homicides/100,000, gun suicides/100,000, unintentional gun deaths/100,000, and undetermined gun deaths/100,000). Gun homicides/100,000: number of gun homicides in one year per 100,000 population. Includes justifiable gun homicides as well as unjustified gun homicides. Gun suicides/100,000: number of gun suicides in one year per 100,000 population. Unintentional gun deaths/100,000: number of unintentional gun deaths in one year per 100,000 population. Undetermined gun deaths/100,000: number of gun deaths in one year per 100,000 population that could not be categorized as homicide, suicide, or unintentional. C. Categorical variables with values calculated from the variables above: Relative guns per person higher – Guns/100 is greater than the median of 10.7 guns/100 population lower – Guns/100 is less than or equal to the median of 10.7 guns/100 population Relative total gun death rate higher – Total gun deaths/100,000 is greater than the median of 1.83 total gun deaths/100,000 population lower – Total gun deaths/100,000 is less than or equal to the median of 1.83 total gun deaths/100,000 population Relative gun homicide rate higher – Gun homicides/100,000 is greater than the median of 0.36 gun homicides/100,000 population lower – Gun homicides/100,000 is less than or equal to the median of 0.36 gun homicides/100,000 population Relative gun suicide rate higher – Gun suicides/100,000 is greater than the median of 0.81 gun suicides/100,000 population lower – Gun suicides/100,000 is less than or equal to the median of 0.81 gun suicides/100,000 population Relative unintentional gun death rate higher – Unintentional gun deaths/100,000 is greater than the median of 0.06 unintentional gun deaths/100,000 population lower - Unintentional gun deaths/100,000 is less than or equal to the median of 0.06 unintentional gun deaths/100,000 population
anderson_instructorSep 1, 20175KB1855
NFL Player Data 2016
This file lists the 2,764 NFL players for all team rosters as of July 22, 2016. Information includes jersey number, name, position, age, height (in inches), weight (in lbs), years in the NFL, college they graduated from, NFL team, position grouping (OL, QB, tailback, TE, WR, Front 7, DB, special teams), side of the football (offensive, defense or special teams), and their experience level by years played.
rlamb@highpoint.eduAug 29, 2017220KB1203
TrafficTickets
These data are from a survey of traffic violations; participants could report on up to 4 incidents. Had Ticket: 0 = No, 1 = Yes; Tickets = Number of tickets received in life; Warnings = Number of warnings (i.e., pulled over but no ticket) in life; Age at incident; Reason for incident; How far over the speed limit the citation was for; Time# and Time both indicate time of day of incident; Road indicates where incident occurred; Utah = Whether incident occurred in Utah (0 = No, 1 = Yes); as well as the make, model, and category of the car.
cvoiseiSep 7, 201726KB557
Titanic Data (Class, Survived, Name, Sex, Age)
Titanic Data Set with the following variables: Name, Sex, Age, Survived, P-Class
smcdaniel04Aug 28, 201768KB788
2017 Fuel Economy Data w Weight & Power - No Hybrids.xlsx
2017 model cars sold in U.S. Subset of original data from EPA Office of Transportation and Air Quality. Removed all trucks, SUVs, and hybrids. Also skipped duplicate vehicles (e.g., 4-dr and 2-dr of same model). Added vehicle weight, hp, torque, and number of passengers.
len.cabrera@sfcollege.eduSep 2, 201790KB199
Hurricane Names Archival Study
In a study, the names of 94 hurricanes were provided to nine independent coders. The coders were not informed that these were hurricane names. The coders were asked to evaluate the perceived masculinity or femininity of the names on two items (1 = very masculine, 11 = very feminine, 1 = very man-like, 11 = very woman-like). These items were averaged for each coder and then averaged across all coders to get the MasFem rating for each hurricane name. Other variables for each hurricane included in the data set are minimum pressure (using two different metrics), the true gender of the hurricane name, category, death toll, normalized damage estimates (NDAM in millions of 2013 dollars) and the elapsed years since the hurricane occurred and the study was conducted.
zbrowderSep 6, 20174KB184
Responses to Self-driving Cars
Respondents provided if they would be comfortable riding in a self-driving car (Comfortable), how many years it would take before self-driving cars were the majority on the road (When), if they expected accidents to increase, decrease, or stay the same when self-driving cars dominate the road (Crashes), their sex (Sex), and their age (Age). The data is then split with a sample of females and their comfort and when and the same with a sample of males.
stjohn314Aug 15, 2017365KB463
Major League Players Elected to Hall of Fame as Players
Includes 2017 inductees Jeff Bagwell, Tim Raines, and Ivan Rodriguez. 31 variables for each player. Team=primary team; BBWAA=Baseball Writers Association of America; Bat: R=right, L=left, B=both; WAR=Wins Against Replacement: number of wins the player added to the team above what an "average" replacement player would add. CS=caught stealing. OPS=On-base Plus Slugging; as a rule of thumb, a "good" OPS is a value that when divided by 3 results in a value that would be considered a "good" batting average. Other variables are hopefully self-explanatory.
treilandJun 5, 201734KB2980

1 2 3 4 5 6 7 8 9 10   >

Always Learning