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Showing 1 to 15 of 115 data sets matching ANOVA
Data Set/Description Owner Last edited Size Views
Bossanova Chevy Nova f
Fictional Data. Four brands of selt belts are compared. Each row is a different date and the number of "approximate deaths" of crash test dummies per 50 trials.
aestepaNov 13, 201926KB208
Recent Weekly Gas Prices (Stacked)
Weekly Retail Gasoline and Diesel Prices http://www.eia.gov/dnav/pet/pet_pri_gnd_a_epm0_pte_dpgal_w.htm 09:14:16 GMT-0400 (Eastern Daylight Time) Source: U.S. Energy Information Administration Stacked for use with two-way ANOVA
sbroadJun 27, 20122KB1065
email survey data-#devices divided into groups 1, 2, &3 (1=1 device, 2=2 devices, 3= 3 or more devices)
I divided our sample of 155 into 3 groups: group 1= those who use 1 device to read email group 2= those who use 2 devices to read email group 3= those who use 3 or more devices to read email
koareyDec 4, 20122KB1603
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
Seating Choice versus GPA (Stacked & Split Columns for Front & Back Rows)
This dataset contains hypothetical (I believe) data on GPA for students who sit in the front and back row of a classroom. The data are shown in several ways: (a) two separate columns (one for the front row GPA and another or the back row GPA); (b) stacked with one column to indicate front or back row and another column with the GPAs; and (c) the row column repeated as a 0/1 indicator variable. This dataset is useful for comparing the different ways that StatCrunch can compare the means of two groups: (a) The two columns of scores (front and back) can be used in the 2-sample t-test or a one-way ANOVA; (b) the stacked text column (front/back) with a separate column for GPA can also be used for one-way ANOVA; and (c) the 0/1 indicator column and stacked GPAs can be used with correlation and regression. Every procedure gives the same p-value and same conclusion, thus highlighting the similarity of statistical procedures and StatCrunch's flexibility.
bartonpoulsonApr 7, 2010465B2858
Granola comparison
Ten subjects in this fictional study were each asked to sample three kinds of granola cereal, labelled simply "A", "B", and "C", and to rate the granola's taste on a scale of 1 to 10. Each subject was given the three granola samples in random order.
statcrunchhelpApr 19, 2016223B1064
Telephone Holding Times
An airline has a toll-free phone number that they use for reservations. Sometimes callers have to be placed on hold. The airline conducted a randomized experiment to determine if there was a significant difference in how long a caller would remain on hold depending on what is playing on the call. The airline randomly selected one out of every 1000 calls to be placed on hold with either a advertisement of current promotions, with muzak playing (elevator music), or with classical music playing. Total, 15 callers were sampled for this study. Each column is the number of minutes that the random caller remained on the line until they hung up for each type of recorded message. This data set comes from "Statistics: The Art and Science of Learning from Data" by Alan Agresti and Christine Franklin.
statcrunchhelpSep 17, 201485B1793
semeat.xls
SOURCE: David H. Holben, “Selenium content of Venison, Squirrel, and beef purchased or produced in Ohio, a low selenium region of the United States,” Journal of Food Science, 67 (2002), 431-433. Testing selenium level for four meats (type) found in Appalachia Ohio. VEN is venison meat, SQU is squirrel meat, RRB is region-raised beef, NRB is non-region raised beef. The outcome variable is selenium (selen)content in ug/100g.
jph422Jan 30, 20081KB445
RSCH665 ANOVA Headphones
In class ANOVA problem for RSCH 665, Module 6.
mark.wiseJul 6, 2016159B240
Split of Hand_washing ANOVA.txt
Bacteria counts on hands after using the labeled hand-cleansing method. Assume a randomized experiment.
kfoong321Feb 7, 2019267B174
Blue Jean anova data
Number of pairs of blue jeans sewed for each worker in a factory. The workers were randomly assigned to work in a cool, moderate, or warm room.
cryan77Nov 26, 2019110B3
KCC ANOVAmillermtNov 21, 20191KB171
ANOVA quizlumanhNov 19, 2019118B38
VCU ANOVA - class examplespburchOct 16, 2019702B2789
Bone 2-way unbalanced ANOVA with Ortho contrasts
The first 3 columns (Growth, Gender, Bone) can be used to demonstrate Unbalanced 2-way Anova. The same results can be obtained using MLR with Growth as Y var and last five columns (g1, b1, b2, g1*b1, g1*b2) as X vars. Run subsets and subtract the Model SS of each subset from Model SS with all 5 vars. This will match the Anova.
statcrunchhelpJun 25, 2015422B830

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