Intro Stats, Books a la Carte Edition (5th Edition)
Intro Stats, Books a la Carte Edition (5th Edition)
5th Edition
ISBN: 9780134210285
Author: Richard D. De Veaux, Paul Velleman, David E. Bock
Publisher: PEARSON
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Chapter 1, Problem 38E

(Exercises 27–40) For each description of data, identify the W’s, name the variables, specify for each variable whether its use indicates that it should be treated as categorical or quantitative, and, for any quantitative variable, identify the units in which it was measured (or note that they were not provided).

38. Walking in circles People who get lost in the desert, mountains, or woods often seem to wander in circles rather than walk in straight lines. To see whether people naturally walk in circles in the absence of visual clues, researcher Andrea Axtell tested 32 people on a football field. One at a time, they stood at the center of one goal line, were blindfolded, and then tried to walk to the other goal line. She recorded each individual’s sex, height, handedness, the number of yards each was able to walk before going out of bounds, and whether each wandered off course to the left or the right. No one made it all the way to the far end of the field without crossing one of the sidelines. (Source: STATS No. 39, Winter 2004)

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The following table shows a data set containing information for 25 of the shadow stocks tracked by the American Association of Individual Investors (aaii.com, February 2002). Shadow stocks are common stocks of smaller companies that are not closely followed by Wall Street analysts. Click on the datafile logo to reference the data. DATA file Company DeWolfe Companies Exchange Ticker Symbol Market Cap ($ millions) Price/ Gross Profit Earnings Ratio Margin (%) AMEX DWL 36.4 8.4 36.7 North Coast Energy OTC NCEB 52.5 6.2 59.3 Hansen Natural Corp. OTC HANS 41.1 14.6 44.8 MarineMax, Inc. NYSE HZO 111.5 7.2 23.8 Nanometrics Incorporated OTC NANO 228.6 38.0 53.3 TeamStaff, Inc. OTC TSTF 92.1 33.5 4.1 Environmental Tectonics AMEX ETC 51.1 35.8 35.9 Measurement Specialties AMEX MSS 101.8 26.8 37.6 SEMCO Energy, Inc. NYSE SEN 193.4 18.7 23.6 Party City Corporation OTC PCTY 97.2 15.9 36.4 Embrex, Inc. OTC EMBX 136.5 18.9 59.5 Tech/Ops Sevcon, Inc. AMEX ΤΟ 23.2 20.7 35.7 ARCADIS NV OTC ARCAF 173.4…
The following table shows a data set containing information for 25 of the shadow stocks tracked by the American Association of Individual Investors (aaii.com, February 2002). Shadow stocks are common stocks of smaller companies that are not closely followed by Wall Street analysts. Click on the datafile logo to reference the data. DATA file Company DeWolfe Companies Exchange AMEX Ticker Symbol Market Cap Price/ Gross Profit Earnings Margin ($ millions) Ratio (%) DWL 36.4 8.4 36.7 North Coast Energy OTC NCEB 52.5 6.2 59.3 Hansen Natural Corp. OTC HANS 41.1 14.6 44.8 MarineMax, Inc. NYSE HZO 111.5 7.2 23.8 Nanometrics Incorporated OTC NANO 228.6 38.0 53.3 TeamStaff, Inc. OTC TSTF 92.1 33.5 4.1 Environmental Tectonics AMEX ETC 51.1 35.8 35.9 Measurement Specialties AMEX MSS 101.8 26.8 37.6 SEMCO Energy, Inc. NYSE SEN 193.4 18.7 23.6 Party City Corporation OTC PCTY 97.2 15.9 36.4 Embrex, Inc. OTC EMBX 136.5 18.9 59.5 Tech/Ops Sevcon, Inc. AMEX ΤΟ 23.2 20.7 35.7 ARCADIS NV OTC ARCAF 173.4…

Chapter 1 Solutions

Intro Stats, Books a la Carte Edition (5th Edition)

Ch. 1 - Prob. 9ECh. 1 - ZIP codes The U.S. Postal Service uses five-digit...Ch. 1 - Voters A February 2010 Gallup Poll question asked,...Ch. 1 - Job hunting A June 2011 Gallup Poll asked...Ch. 1 - Medicine A pharmaceutical company conducts an...Ch. 1 - Stress A medical researcher measures the increase...Ch. 1 - Voting and elections Pollsters are interested in...Ch. 1 - Weather Meteorologists utilize sophisticated...Ch. 1 - (Exercises 1926) For each description of data,...Ch. 1 - (Exercises 1926) For each description of data,...Ch. 1 - (Exercises 1926) For each description of data,...Ch. 1 - (Exercises 1926) For each description of data,...Ch. 1 - (Exercises 1926) For each description of data,...Ch. 1 - (Exercises 1926) For each description of data,...Ch. 1 - (Exercises 1926) For each description of data,...Ch. 1 - (Exercises 1926) For each description of data,...Ch. 1 - (Exercises 2740) For each description of data,...Ch. 1 - (Exercises 2740) For each description of data,...Ch. 1 - (Exercises 2740) For each description of data,...Ch. 1 - (Exercises 2740) For each description of data,...Ch. 1 - (Exercises 2740) For each description of data,...Ch. 1 - (Exercises 2740) For each description of data,...Ch. 1 - (Exercises 2740) For each description of data,...Ch. 1 - (Exercises 2740) For each description of data,...Ch. 1 - (Exercises 2740) For each description of data,...Ch. 1 - (Exercises 2740) For each description of data,...Ch. 1 - (Exercises 2740) For each description of data,...Ch. 1 - (Exercises 2740) For each description of data,...Ch. 1 - (Exercises 2740) For each description of data,...Ch. 1 - (Exercises 2740) For each description of data,...Ch. 1 - Kentucky Derby 2016 on the computer Load the...Ch. 1 - Indy 500 2016 on the computer Load the Indy 500...

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