GOT DATA?

Document created by Tom DeMarco Employee on Jul 19, 2016Last modified by Elizabeth Uva on Jul 21, 2016
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Real data is a hallmark of Freeman/Macmillan texts.  Data sets throughout our introductory statistics texts consist of real data to motivate students and enable them to learn from actual numbers.

 

The index that follows indicates which sets to use for the desired output.

 

Instructions: Find the book you are looking for and click "access data sets" to download the data. If you are looking for a specific type of output such as a time plot or bar chart, use the index below to find it.

 

From Basic Practice of Statistics, 7e

 

 

 

Access Data Sets

From Discovering Statistics, 3e 

 

 

 

Access Data Sets

From Introduction to the Practice of Statistics, 8e

 

 

Access Data Sets

From Introductory Statistics, 2e

 

 

 

Access Data Sets

From Practice of Statistics for Business and Economics, 4e

 

Access Data Sets

From Practice of Statistics in the Life Sciences, 3e

 

 

Access Data Sets

Time ploteg01-12collegex, ex01-39furseals, ex01-45ozoneta02-37murderrate, ta02-17harrassment, ta02-18petitlarceny5ex01-30energy-eg01-12tbillex01-11, ex01-36, ex01-40
Bar charteg01-02majors, eg01-03music, ex01-26socialnt, ex01-29canadata02-11countysections, ta02-13nevadacounties, ta02-14winterolympics, ta02-15worldwaterex01-25titanic, ex01-32favcol, ex01-33lfavcol, ex01-34garbage, ex01-36browsed, ex01-37browsemex02-21contract, ex02-22dairy, ex02-26psychgrid, ex02-27icecream, ex02-28tablesawex01-18canadap, ex01-26garbage, ex01-27browser, ex01-29facebk, ex01-30facebkex01-26, ex01-27, ex01-28, ex01-29, eg01-07
Histogrameg01-04gradrate, ex01-34foodoils, ex01-035nursesta02-26tradebalance,
ta02-27theftrate20
ex01-29twittc, ex01-73crp, ex01-72pines, ex16-14calls80ex02-91penalty, ex02-90yarn, ex02-88diamond, ex02-95carcost, ex03-92cubetimeex01-106bestbus, ex01-107bestbus, ex01-110tbill50ex01-05, ex01-33, ta01-2, ex01-36
Scatterplotex04-30sulfur, eg04-32canary04sqfootsale, ex04-35videogamereg, ex04-36edunemploy, ex04-37dartsdija ex04-38ageheight, ex04-39gardasilregex02-12laundry, ex02-13laundry, ex02-18armstr, ex02-22decayeg12-01golf, eg12-04noise, ex12-32hunger, ex12-33cholesteg02-05edspend, ex02-014canadap, ex02-015canadap, ex02-019tts, ex02-012beerex03-25, ex03-24, ex03-23, ta03-03, ta03-04
Boxploteg02-07midcars, ex02-43gastricta03-28nasdaqstock, ta03-24dietarysupp, ex03-59dartsex01-55stat, ex01-63stout, ex01-66smolts, ex01-72pinesex03-116jury, ex03-112storms, ex03-113amberlit, ex03-127cubelux, ex03-126readingex01-42acct, eg01-25cc80, eg01-26tbilljjex01-37, Large.FEV (Ch. 2), Large.Calcium (Ch. 2)
Pareto chartex31-04drg, ex31-06operate, ex31-47complaint, ex31-51paintta02-15worldwater, ta02-16cartypemodel--ex01-19canadap, eg01-11bcosts,eg01-03
Pie chartex01-26socialnt, ex01-2majorsta02-11countysections, ta02-13nevadacounties, ta02-15worldwater, ta02-16cartypemodelex01-26titanic, ex01-34garbage, ex01-36browsed,ex01-37browsemex02-23carsatis, ex02-24voting, ex02-25prizect, ex02-26psychgrid, ex02-27icecreamex01-26garbage, eg01-09online, eg01-10bcostseg01-03
Stem-and-leaf display (stemplot)eg01-11health, ex01-36co2emiss, ex01-37furseals, ex02-11dataset2ta02-26tradebalance,
ta02-27theftrate20
ex01-28twittc, ex01-41facer, ex01-43sevengr, ex01-66smoltsex02-57watemp, ex02-56calburn, ex02-55reactme, ex02-58luxmeasex01-39gdpa, ex01-44acctex01-09, ex01-10, ta01-3, ex01-36, ex01-37
Simpson's paradoxex06-06bsktball, ex06-07jury, ex06-25discrim-eg02-42custser, ex02-167admits, ex02-168simregex03-106arrival, ex03-112storms, ex03-115vitc, ex03-117taxlisteg02-29cserv, ex02-101hospex05-29, ex05-07, ex05-08
Outliersex02-06seahawks, ex02-50gradrateeg03-29nutrition, ex03-81breakfastcal, ex03-115pedestrianseg01-16calls, ex01-23stat, ex01-19collegeta02-02ex01-33tts25, ex02-17decay, ex02-19tts-
Area chart------
Control chartex31-30mount, ex31-22drg-ex17-54joewgt, ex17-21mounting, ex17-36drg-ex12-47school, ex12-50poerr, ex12-58hloss, ex12-59bone, ex12-61fthrow-
R chartex31-55rtimes---eg12-02lab, eg12-03oring, ex12-28alloy, ex12-58hloss-
S chartex31-14hard2, ex31-16mount, ex31-21monitrs-eg17-05h2ores, ex17-21mount-eg12-04lab, ex12-14hloss, ex12-59bone, ex12-55film-
x̅ chartex31-11hard, ex31-14hard2, ex31-16mount, ex31-21monitrs-eg17-05h2ores, ex17-17pill, ex17-21mount-eg12-04lab, ex12-14hloss, ex12-28alloy, ex12-56film-
Univariate analysis---ex13-14eyes, ex13-15homes, ex13-16dinner, ex13-17lettuce, ex13-18h1n1, ex13-19employed--
Bivariate analysis---ex13-42casino, ex13-43tasty, ex13-44writing, ex13-45radio, ex13-46homework, ex13-48resort--
Resampling--ex16-01-time6, ex16-03stout6---
Large data setsonline07-01satact, online07-02mlb, online07-03phil, online 07-05whatgoals (Ch. 2), cafe (Ch. 2), New York (Ch. 2), petit larceny (Ch.2), Titanic(Ch.2), Nutrition (Ch. 3, 4, 7, 9, 10, 13, 14), Gardasil (Ch. 5), Fuel Efficiency (Ch. 7), Restaurants (Ch. 9), Texas (Ch. 9), Crash (Ch. 12, 13), Baseball 2013 (Ch. 13)eg01-16calls, eg01-36titanic, ex01-165berries, ex10-43perfpay, ex12-72dandruff, eg13-08hrtrate, ex01-146canfregex12-246fisheg01-14cc, ex02-21canfuel, ex10-23inageLarge.Bodyfat (Ch. 1), Large.Everglades (Ch. 1), Large.FEV (Ch. 2), Large.Calcium (Ch. 2)

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