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Showing 1 to 15 of 263 data sets matching mean
Data Set/Description Owner Last edited Size Views
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, 20171MB11686
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, 2017919KB10338
Movie Budgets and Box Office Earnings (Updated Spring 2018)
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.

statcrunch_featuredOct 4, 2018270KB15094
FIFA World Cup Mens Players 2018
This data set records information for all 736 players for the 2018 FIFA World Cup. Included for each player is their national team (Team) along with their club team (Club).
statcrunch_featuredAug 1, 201863KB3878
California Home Prices, 2009
This dataset is a collection of real estate listings from San Luis Obispo county, California, and some locations around it from 2009. The prices are their list price at the creation of this dataset. For more information about this data, go to the website source listed above.
statcrunch_featuredApr 3, 201746KB8557
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, 201710KB2960
All MLB Salaries (1985-2015)
This data has all MLB player salaries between 1985-2015 including the team played for, the city, and a unique ID for each player. Total this includes 25,575 salaries for 4,963 different baseball players.
The player ID is the first 5 letters from the last name, followed by the first two letters from the first name, followed by a number in case of duplicate names. For example, bondsba01 stands for Barry Bonds with "01" because he's the first with the "bondsba" name ID.
statcrunch_featuredJun 27, 20171MB5240
Roller Coasters Data
This dataset looks at some of the roller coasters across the US and various other countries.
ColumnDescription
NameName of roller coaster
ParkAmusement park for roller coaster
CityCity for amusement park
StateState abbreviation
CountryCountry of the roller coaster. US: United States, MX: Mexico, CR: Costa Rica, GT: Guatemala, CO: Columbia, VE: Venezuela, BR: Brazil, AR: Argentina, CL: Chile, EQ: Ecuador, PE: Peru, F: France, D: Germany
TypeS: Steel, W: Wood
ConstructorType of build for the roller coaster
HeightHeight in meters
SpeedSpeed in kilometers per hour (km/h)
LengthLength in meters
InversionsYes if there are inversions, no if not
DurationDuration of ride in seconds
GForceMax g-force
OpenedYear it opened
RegionGeographic region for the roller coaster
statcrunch_featuredApr 3, 201748KB6876
Nutritional Data for Fast Food 2017
The dataset was collected in January of 2017 by looking through online nutritional information provided by fast food restaurant chains. Nutrition data on various burgers, a breaded chicken sandwich, a grilled chicken sandwich, chicken nuggets, french fries, and a chocolate milkshake were collected for each restaurant (when applicable). For each chain the smallest hamburger, the smallest cheeseburger, and a variety of their most well known larger burgers were selected.
statcrunch_featuredSep 12, 201711KB16325
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, 20174KB8002
Body Temperature
Data taken from the Journal of Statistics Education online data archive. That archive in turn got the data from an article in the Journal of the American Medical Association. (Mackowiak, et al., "A Critical Appraisal of 98.6 Degrees F …", vol. 268, pp. 1578-80, 1992).
"Body Temp" is measured in degrees fahrenheit
"Heart rate" is the resting beats per minute
statcrunch_featuredJun 27, 20172KB13912
D4.3
Population A, mean=36, sd=4. Population B = 44 (single value) Explore how to compute this test using StatCrunch.
housew1Jun 16, 201946KB58
D2.4
Data set with a mean =40 and SD = 10. Explore how z-scores were computed. You will see [8] above the StatCrunch button. Explore the tables visuals, and calculated columns (Z-score and DATA2).
housew1Jun 16, 201953KB53
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, 2017266KB6121
Daily average temperatures for Houston and Raleigh over several years
Daily average temperatures are provided form January 1, 1995 to November 19, 2012. The daily average is calculated as the mean of 24 hourly readings. Values of -99 represent missing values. Which city is typically hotter? How well can you predict the average in one city using the average from the other? Should your predictions depend on the season?
websterwestDec 6, 2012125KB1575

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