StatCrunch logo (home)

Data sets shared by StatCrunch members
Showing 1 to 15 of 146 data sets matching actor
Data Set/Description Owner Last edited Size Views
Oscar Winner Ages Males and Females for 90 years of the 91 years Oscar has been in existance
This is an updated list of all Oscar winning actresses and actors from the very first Oscar awarded (1927) to present (2017). As of today (02/11/18), the 2018 Oscars have not occurred. That is the reason that 2018 is not included in this comprehensive list.
elizabeth.flynnFeb 11, 20191KB369
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, 2008450KB3143
Movie Budgets and Box Office Earnings (Updated Fall 2016)
This data all comes from the following website the tracks the financial performance of movies:
http://www.the-numbers.com/movie/budgets/all

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

ntorno8Jun 30, 2017266KB5917
Top Rated Jobs 2014
This data is gathered from careercast.com 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.

ColumnDescription
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, 20169KB2764
Guns Ownership and Deaths by Firearms by State

The composite of two datasets from StateMaster.com, this dataset shows the percentage of survey respondents* who indicated that there is a firearm in the home [http://www.washingtonpost.com/wp-srv/health/interactives/guns/ownership.html] and the number of deaths by firearms per 100,000 population (most recent) [http://www.statemaster.com/graph/cri_mur_wit_fir-death-rate-per-100-000].

*In 2001 the Behavioral Risk Factor Surveillance System (BRFSS) in North Carolina surveyed 201,881 respondents nationwide, asking them, "Are any firearms now kept in or around your home? Include those kept in a garage, outdoor storage area, car, truck, or other motor vehicle."

mshelly33702Aug 29, 20102KB3982
Diamond Ring Prices.xls
The source of the data is a full page advertisement placed in the Straits Times newspaper issue of February 29, 1992, by a Singapore-based retailer of diamond jewelry. The advertisement contained pictures of diamond rings and listed their prices, diamond content, and gold purity. Only 20K ladies' rings, each mounted with a single diamond stone, were considered for this study. 20K rings are made with gold of 20 carat purity. (Pure gold is rated as 24K.) There were 48 such rings of varying designs. The weights of the diamond stones ranged from 0.12 to 0.35 carats (a one carat diamond stone weighs 0.2 gram) and were priced between $223 and $1086. The jewelry store adopted a fixed-price policy. How Is Jewelry Priced? In Singapore, the pricing of gold jewelry is simple. The price equals the current market value of the gold content (i.e., weight times the going rate per gram of gold) plus a craftsmanship fee. However, the pricing of other jewelry like diamond rings is more complicated because they are not as standardized as gold jewelry. The price of diamond jewelry depends on the four C's: caratage, cut, colour, and clarity of the diamond stone. A good cut gives a diamond more sparkle. Colourless diamonds are the most prized. A flawless diamond has maximum clarity because the passage of light is unimpeded through the stone. Cut, colour, and clarity are subjective factors and are very hard for the layman to gauge.
craig_slinkmanApr 22, 2010586B2614
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, 20101KB5497
Final Stats Project
I set out to see if age or gender were factors in the average amount of exercise people participated in per week.
haleymcsweeneyMay 15, 2010195B1320
diamonds.csv
This is a very large data set showing various factors of over 50,000 diamonds including price, cut, color, clarity, etc. price: price in US dollars ($326–$18,823) carat: weight of the diamond (0.2–5.01) cut: quality of the cut (Fair, Good, Very Good, Premium, Ideal) color: diamond colour, from J (worst) to D (best) clarity: a measurement of how clear the diamond is (I1 (worst), SI1, SI2, VS1, VS2, VVS1, VVS2, IF (best)) x: length in mm (0–10.74) y: width in mm (0–58.9) z: depth in mm (0–31.8) depth: total depth percentage = z / mean(x, y) = 2 * z / (x + y) (43–79) table: width of top of diamond relative to widest point (43–95)
hbarker2Feb 19, 20163MB2072
Low Birth Weight Study
SOURCE: Hosmer and Lemeshow (2000) Applied Logistic Regression: Second Edition Data were collected at Baystate Medical Center, Springfield, Massachusetts during 1986. DESCRIPTIVE ABSTRACT: The goal of this study was to identify risk factors associated with giving birth to a low birth weight baby (weighing less than 2500 grams). Data were collected on 189 women, 59 of which had low birth weight babies and 130 of which had normal birth weight babies. Four variables which were thought to be of importance were age, weight of the subject at her last menstrual period, race, and the number of physician visits during the first trimester of pregnancy. LIST OF VARIABLES: Columns Variable Abbreviation ----------------------------------------------------------------------------- 2-4 Identification Code ID 10 Low Birth Weight (0 = Birth Weight >= 2500g, LOW 1 = Birth Weight < 2500g) 17-18 Age of the Mother in Years AGE 23-25 Weight in Pounds at the Last Menstrual Period LWT 32 Race (1 = White, 2 = Black, 3 = Other) RACE 40 Smoking Status During Pregnancy (1 = Yes, 0 = No) SMOKE 48 History of Premature Labor (0 = None 1 = One, etc.) PTL 55 History of Hypertension (1 = Yes, 0 = No) HT 61 Presence of Uterine Irritability (1 = Yes, 0 = No) UI 67 Number of Physician Visits During the First Trimester FTV (0 = None, 1 = One, 2 = Two, etc.) 73-76 Birth Weight in Grams BWT ----------------------------------------------------------------------------- PEDAGOGICAL NOTES: These data have been used as an example of fitting a multiple logistic regression model. STORY BEHIND THE DATA: Low birth weight is an outcome that has been of concern to physicians for years. This is due to the fact that infant mortality rates and birth defect rates are very high for low birth weight babies. A woman's behavior during pregnancy (including diet, smoking habits, and receiving prenatal care) can greatly alter the chances of carrying the baby to term and, consequently, of delivering a baby of normal birth weight. The variables identified in the code sheet given in the table have been shown to be associated with low birth weight in the obstetrical literature. The goal of the current study was to ascertain if these variables were important in the population being served by the medical center where the data were collected. References: 1. Hosmer and Lemeshow, Applied Logistic Regression, Wiley, (1989).
wikipetersonJul 23, 20126KB7544
Home prices in Albuquerque
The data are a random sample of 117 records of resales of homes from Feb 15 to Apr 30, 1993 from the files maintained by the Albuquerque Board of Realtors. This type of data is collected by multiple listing agencies in many cities and is used by realtors as an information base.
ColumnDescription
PRICE Selling price in hundreds of dollars
SQFT Square feet of living space
AGE Age of home in years
FEATS Number out of 11 features (dishwasher, refrigerator, microwave, disposer, washer, intercom, skylight(s), compactor, dryer, handicap fit, cable TV access)
NE Located in northeast sector of city (1) or not (0)
COR Corner location (1) or not (0)
TAX Annual taxes in dollars
statcrunchhelpSep 4, 20143KB2504
Violent Crimes by State
http://www.census.gov/statab/ranks/rank21.html State Rankings -- Statistical Abstract of the United States VIOLENT CRIMES 1 PER 100,000 POPULATION -- 2006 [When states share the same rank, the next lower rank is omitted. Because of rounded data, states may have identical values shown, but different ranks. Cautionary note] Cautionary note about rankings The ranks in some tables are based on estimates derived from a sample(s). Because of sampling and nonsampling errors associated with the estimates, the ranking of the estimates does not necessarily reflect the correct ranking of the unknown true values. Thus, caution should be used when making inferences or statements about the states' true values based on a ranking of the estimates. As an example, the estimated total (average, percent, ratio, etc.) for State A may be larger than the estimates for all other states. This does not necessarily mean that the true total (average, percent, ratio, etc.) for State A is larger than those for all other states. Such an inference typically depends on --among other factors-- the size of the difference(s) between the estimates in question, and the size of their associated standard errors. In other tables, the ranks are based on a complete enumeration of the target population, or on complete administrative reporting from the population. In such cases, sampling is not used, and there is no sampling error component in the estimates. Still, care should still be taken when making inferences or statements based on the rankings. The table values may still exhibit nonsampling error originating from such sources as coverage problems (missing units or duplicates), nonresponse, misreporting, and others. Last Revised: September 27, 2011 at 09:43:17 AM
phil_larsonJan 16, 2013881B3332
Marriage vs The Economy
Comparing numbers of marriages in the last 30 years to the following factors of the economy: GDP Growth, Unemployment rate, Median Hourly Wages, and Total National Student Aid and Loans
sma25908Oct 24, 20181KB544
Albuquerque NM Real Estate Prices
Description: The data are a random sample of records of resales of homes from Feb 15 to Apr 30, 1993 from the files maintained by the Albuquerque Board of Realtors. This type of data is collected by multiple listing agencies in many cities and is used by realtors as an information base. Number of cases: 117 Variable Names: PRICE = Selling price ($hundreds) SQFT = Square feet of living space AGE = Age of home (years) FEATS = Number out of 11 features (dishwasher, refrigerator, microwave, disposer, washer, intercom, skylight(s), compactor, dryer, handicap fit, cable TV access NE = Located in northeast sector of city (1) or not (0) COR = Corner location (1) or not (0) TAX = Annual taxes ($)
craig_slinkmanApr 11, 20102KB601
Diamonds
This is a very large data set showing various factors of over 50,000 diamonds including price, cut, color, clarity, etc. price: price in US dollars carat: weight of the diamond cut: quality of the cut (Fair, Good, Very Good, Premium, Ideal) color: diamond colour, from J (worst) to D (best) clarity: a measurement of how clear the diamond is (I1 (worst), SI1, SI2, VS1, VS2, VVS1, VVS2, IF (best)) x: length in mm, y: width in mm, z: depth in mm, depth: total depth percentage = z / mean(x, y) = 2 * z / (x + y), table: width of top of diamond relative to widest point
gjohnson151515Jan 12, 20173MB697

1 2 3 4 5 6 7 8 9 10   >

Always Learning