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Data Set/Description Owner Last edited Size Views
National Longitudinal Youth Survey: Weight Perception
The Youth survey consists of a nationally representative sample of youths who were 14 to 20 years old as of December 31, 1999.
This dataset tracks the Age, Height (in inches), Weight (in pounds), Gender, and the self reported "How would you describe your weight?" multiple choice answers for the individuals.
statcrunch_featuredNov 10, 2017330KB9750
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, 20174KB9181
Times World University Rankings (2011-2016)
This data comes from the annual Times magazine rankings of universities across the world. The webpage for the Times 2016 rankings is listed above in the source.
The formula for the 2016 rankings is as follows:
30% for Teaching Rating
7.5% for International Outlook Rating
30% for Research Rating
30% for Citations Rating
2.5% for Industry Income Rating.
The “Total Score” from 2016 can be recreated using this formula.

World_RankUniversity rank for a given year
University_NameThe name of the university
CountryLocation of university
Teaching_Rating Rating from a 0-100 scale of the quality of teaching at the university. This rating is based on the institution’s reputation for teaching, it’s student/staff ratio, it’s PhD’s/ undergraduate degrees awarded ratio, and it’s institutional income/ academic staff ratio.
Inter_Outlook_Rating Rating from a 0-100 scale of the international makeup of a university. This rating is based the international student percentage, international staff percentage, and the percentage of research papers from the university that include at least one international author.
Research_Rating Rating from a 0-100 scale of quality of research at the university. This rating is based on the university’s reputation, it’s research income/ academic staff ratio, and it’s production of scholarly papers.
Citations_Rating Rating from a 0-100 scale of based on the normalized average of citations by other papers per paper from the university (how often the research from the university is cited by other papers).
Industry_Income_Rating Rating from a 0-100 scale grading how much companies are willing to invest in the universities research. The rating is calculated based on the research income from businesses per academic staff member.
Total_ScoreThe final score used to determine the university ranking based on Teaching_Rating, International_Outlook_Rating, Research_Rating, Citations_Rating, and Industrial_Income_Rating.
Num_StudentsTotal number of students in a given year
Student/Staff_RatioNumber of students per academic staff member
%_Inter_StudentsPercentage of student body who come from a foreign county
%_Female_Students Percentage of student body that is female.
YearAcademic year that the ranking was released. For example, 2016 denotes the 2015-2016 academic year.
statcrunchhelpApr 5, 2016254KB4207
Advanced NBA Statistics for 2013-2014 Season
N = 342; only players with at least 40 games played are included. These are advanced metrics which attempt to evaluate, relatively speaking, how good an NBA basketball player was during the 2013-2014 (in which Kevin Durant won the MVP Award). Variables..........Position -- what position did they play?..... Age -- How old was the player as of February 1, 2014?..... Team -- Obvious..... PER -- Player Efficiency Rating; a measure of per-minute production standardized such that the league average is 15..... TS -- True Shooting Percentage; a measure of shooting effeciency that takes into account 2-point field goals, 3-point field goals, and free throws..... ORB -- Offensive Rebound Percentage; an estimate of the percentage of available offensive rebounds a player grabbed while he was on the floor..... DRB -- Defensive Rebound Percentage; an estimate of the percentage of available defensive rebounds a player grabbed while he was on the floor..... TRB -- Total Rebound Percentage; an estimate of the percentage of available rebounds a player grabbed while he was on the floor..... AST -- Assist Percentage; an estimate of the percentage of teammate field goals a player assisted while he was on the floor..... STL -- Steal Percentage; an estimate of the percentage of opponent possessions that end with a steal by the player while he was on the floor..... BLK -- Block Percentage; an estimate of the percentage of opponent two-point field goal attempts blocked by the player while he was on the floor..... TOV -- Turnover Percentage; an estimate of turnovers per 100 plays..... USG -- Usage Percentage; an estimate of the percentage of team plays used by a player while he was on the floor..... ORtg -- Offensive Rating: An estimate of points produced (players) or scored (teams) per 100 possessions..... DRtg -- Defensive Rating: An estimate of points allowed per 100 possessions..... OWS -- Offensive Win Shares; an estimate of the number of wins contributed by a player due to his offense..... DWS -- Defensive Win Shares; an estimate of the number of wins contributed by a player due to his defense..... WS -- Win Shares; an estimate of the number of wins contributed by a player.
daniel.inghramMay 22, 201433KB4300
Top Rated Jobs 2014
This data is gathered from and is available in it's original form at the source listed above. The dataset originally was created by Keisha Brown from Georgia Perimeter College.

Ranking Ranking from 0 to 200 based on the combined “Overall Rating”
JobTitle for the job.
Median Annual IncomeBased on Bureau of Labor Statistics
Overall RatingCombined rating based on income, stress, hiring outlook, and work environment. The lower the rating the better rated the job.
Stress RatingA rating from 1 to 200 estimating the overall stress level from the job. This essentially is a ranking with 1 being the least stressful job and 200 being the most stressful job.
Hiring Outlook Rating A rating from 1 to 200 estimating the overall stress level from the job. This essentially is a ranking with 1 being the best hiring outlook and 200 being the worst hiring outlook.
Work Environment Rating A rating from 1 to 200 estimating the overall stress level from the job. This essentially is a ranking with 1 being the best work environment and 200 being the worst work environment.
statcrunchhelpMar 14, 20169KB3118
IMDB Movie Database
This data set is a collection of information of over 50,000 movies that are listed on These are all movies before 2005. The data set includes titled, year, length, budget, rating, votes(number of imdb users that rated the movie), r1-10(percentile to nearest 10% of votes who gave the movie a 1), the mpaa rating, and a number 1 given if the movie is a action, animation, comedy, drama, documentary, romance, or short.
hbarker2Jan 9, 20176MB2980
Graduate Admissions
The dataset contains several parameters which are considered important during the application for Masters Programs. The parameters included are : 1. GRE Scores ( out of 340 ) 2. TOEFL Scores ( out of 120 ) 3. University Rating ( out of 5 ) 4. Statement of Purpose and Letter of Recommendation Strength ( out of 5 ) 5. Undergraduate GPA ( out of 10 ) 6. Research Experience ( either 0 or 1 ) 7. Chance of Admit ( ranging from 0 to 1 )
brmorganteJan 15, 201912KB1435
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.
websterwestJun 3, 20144KB1079
Cereal nutrition
Name: Name of cereal, Manu: Manufacturer of cereal, Target: Target audience for cereal (adult, child), Shelf: Display shelf at the grocery store, Calories: Calories per serving, Carbs: Grams of complex carbohydrates in one serving, Fat: Grams of fat in one serving, Fiber: Grams of dietary fiber in one serving, Potassium: Milligrams of potassium in one serving

Protein: Grams of protein in one serving, Sodium: Milligrams of sodium in one serving, Sugars: Grams of sugars in one serving, Vitamins: Vitamins and minerals - 0, 25, or 100% of daily need in one serving, CRRating: Consumer Report rating, Cups: Number of cups in one serving, Weight: Weight in ounces of one serving

cdcummings12Sep 15, 20112KB3506
Seating Choice versus GPA (For 3 rows, with Text and Indicator Columns)
This dataset contains hypothetical (I believe) data on GPA for students who sit in the front, middle, and back rows of a classroom, as well as a hypothetical gender variable. The data are shown using both text variables (e.g., "front" and "middle") and 0/1 indicator variables for the row and gender variables. This dataset is useful for demonstrating the different ways that StatCrunch can compare means based on two factors: (a) the text factor columns can be used in a two-way ANOVA; and (b) the 0/1 indicator columns can be used in multiple regression. (Because of StatCrunch's current limitation on equal cells, the 0/1 variables only use the first and middle rows.) Both procedures gives the same p-value and same conclusion (as long as the interaction term is centered), thus highlighting the similarity of statistical procedures and StatCrunch's flexibility.
bartonpoulsonApr 7, 20101KB5970
IMDB Movie Ratings
This data set contains the title, original year of production, the number of user votes, and the average user rating for a number of movies listed at The data set also contains the source of the content, which unless otherwise noted is a film released for theaters. The data set does contain a number of items made for television including awards shows and also movies that went straight to a video release. The data set is restricted to relatively popular movies obtaining at least 500 votes. It was created using data that was current as of May 28th, 2014 and revised to remove video games on June 2nd, 2014.
websterwestSep 29, 20141MB1417
Top Grossing Movies Coded for Content.xls
Data were gathered for the top grossing movies for 2004-2009. MPAA ratings, critics ratings, genre, and gross receipts. In addition, data were gathered from the Kids in Mind website on whether the movies included sex/nudity, violence, and profanity (all on a 1-10 scale). We also coded the movies (0 = No, 1 = Yes) for the presence of racism, class discrimination, adult topics, and drug use.
green.williamdApr 15, 20102KB845
IMDB Movie Ratings
Random sample of 2410 movies from IMDB webpage.
cecil_collegeJul 8, 201480KB3806
Responses to Favorite Web Browser
Respondents provided their favorite web browser, the operating system (OS) they use most often, their age and their gender.

Check out the original survey:

Feel free to copy and use in your own course.

scsurveyFeb 18, 201314KB1042
Jealousy file.xlsx
Do men and women differ in jealousy about their romantic partners? Research by Buss, Larsen, Westen, and Semmelroth (Exp. 1, 1992) suggested that the answer is yes. In that study, heterosexual men and women in the United States imagined their romantic partners engaged in emotional or sexual affairs with another person, and then indicated which scenario would be more upsetting to them. Men reported being more distressed when imagining their partners involved in sexual infidelity, whereas women were more distressed when they imagined their partners involved in emotional infidelity. Buss et al. concluded that their findings supported their hypotheses, which were derived from evolutionary theory. Subsequent research either supported the Buss et al. (1992) findings or found limitations to their conclusions (Harris, 2003). For example, although Buss et al. used a forced-choice method in their study (e.g., “Which of these two scenarios is more upsetting?”), others have not found such clear sex differences when rating scales are used instead (DeSteno, Bartlett, Braverman, & Salvoes, 2002). In addition, cultural differences have also been found. For example, European and Asian men are more likely to choose emotional infidelity as worse, compared to American men (Harris, 2004). The purpose of this study was to see if (a) we would replicate the original Buss et al. (1992) findings using an Australian sample in 2015, and (b) whether asking participants to rate their feelings would reveal the same sex differences that were reported in the original work. We therefore had separate hypotheses regarding the differences between men and women with respect to emotional infidelity and sexual infidelity.
e.vanmanMay 7, 20177KB1125

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