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Data Set/Description Owner Last edited Size Views
Movie Budgets and Box Office Earnings (Updated Spring 2018)
This data all comes from the following website the tracks the financial performance of movies:

The “Budget”, “Domestic Gross”, and “Worldwide Gross” columns each are in millions of dollars.

statcrunch_featuredOct 4, 2018270KB14115
Oscar nominations
The data set contains the year, category, nominee and whether they won for all academy award nominations from 1927 through 2006. A good exercise is to use StatCrunch to compute the number of nominations for each actress in the ACTRESS (all caps) category along with the first and last year they were nominated.
websterwestMar 10, 2008450KB3258
Movie Budgets and Box Office Earnings (Updated Fall 2016)
This data all comes from the following website the tracks the financial performance of movies:

The “Budget”, “Domestic Gross”, and “Worldwide Gross” columns each are in millions of dollars.

ntorno8Jun 30, 2017266KB6051
2016 Movie Data
2016 movies (142) with budget and domestic gross (both in millions)
mooresk1Sep 21, 20175KB1690
Marvel vs. DC at the Box Office
This data set contains information on how the two comic book companies have faired at the box office. Each movie from both Marvel and DC is listed with name of the film and release date. The Domestic and Foreign gross of each film is provided in millions of dollars along with the total Worldwide gross. The Adjusted column modifies this total for inflation.
websterwestAug 23, 20144KB2866
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, 20176MB2758
Data from an Introductory Statistics Class
Students in an introductory statistics class were asked to fill out a data sheet, creating the following variables. Height -- height of the student measured in inches; Gender -- student's gender (male or female); Shoes -- the number of pairs of shoes that the student owns; Number -- the student was asked to choose a number between 1 and 10; Dvds -- the student was asked how many DVD's did he or she own; ToSleep -- time (to the nearest half hour) did you go to bed last night? (this was converted to the number of hours past midnight); WakeUp -- -- time (to the nearest half hour) did you wake up this morning? (this was converted to the number of hours past midnight); NOTE: One can complete the hours of sleep by the computation HoursSleep = WakeUp - ToSleep; Haircut -- answer to "How much did you spend on your last haircut (including the tip)?"; Job -- answer to "How many hours do you plan to work on a job per week this semester?; Drink -- answer to "For an evening meal, do you prefer water, soda (pop), milk?" This was recorded as water, soda, pop, or blank.; SleeplessInSeattle -- the student was asked to rate the movie "Sleepless in Seattle" on a scale from 1 to 10. The answer is blank if he or she did not see the movie.; Pirates -- the student was asked to rate the movie "Pirates of the Caribbean" on a scale from 1 to 10. The answer is blank if he or she did not see the movie.
bayesballApr 13, 200867KB6509
Actress oscar nominations
Nominations for all actresses through 2006
websterwestMar 10, 200812KB1846
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, 20141MB1311
Facebook Friend Data
This data set contains information about my Facebook friends and contains the following 23 variables: 1. First Name 2. Last Name 3. Gender 4. Relationship Status 5. Birth Month 6. Birth Date 7. Birth Year 8. Age 9. Wall Posts 10. Location 11. Hometown 12. # of Movie Likes 13. Movie Likes 14. # of Music Likes 15. Music Likes 16. # of TV Likes 17. TV Likes 18. # of Book Likes 19. Book Likes 20. # of Colleges 21. Colleges 22. Facebook 23. Name
gloriajanaebaptisteFeb 16, 2013413KB1088
IMDB Movie Ratings
Random sample of 2410 movies from IMDB webpage.
cecil_collegeJul 8, 201480KB3665
2010 Movie Revenue
This dataset has the revenues for each movie released in 2010. Toy Story 3 tops the charts -
cecil_collegeJan 22, 201135KB6313
Baseball data for correlation and regression
This table shows the total number of runs scored, at bats, hits, etc for each of the 30 MLB teams for the 2009-2011 seasons. //// Correlations and linear regression models can be calculated between the different numeric variables. A good exercise is to see which variables correlate most strongly with runs_scored. //// As emphasized in the movie Moneyball, some of the classic metrics such as batting_avg is not as good as the newer metrics like OBP (on base percentage), SLG (slugging percentage), or OPS (on base plus slugging). //// A guide to a few of the variables that may not be self explanatory. Runs_Scored: The total of all runs (points) the baseball team scored by the end of the season. Batting_avg: This is equal to the number of hits divided by at_bats OBP: On Base Percentage. Similar to batting average, except that it takes into account walks and hit-by-pitch. Some players who don't have high batting averages, manage to get walked quite frequently. SLG: Slugging - This weights hits to first base as 1 point, hits to second base as 2 points, third as 3, homeruns as 4, and divides the total by the number of at bats. OPS - On Base Plus Slugging - this is just OBP added to the SLG numbers.
mileschenApr 17, 20126KB4284
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, 20102KB789
Movies IMDB ranked.xlsx
Statistics for the Social Sciences, Correlation database
nicholspsychologyOct 14, 201713KB601

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