Notes and Data Sources

1. See census.gov.

2. From State of Drunk Driving Fatalities in America 2010, available at centurycouncil.org.

3. James P. Purdy, “Why first-year college students select online research sources as their favorite,” First Monday 17, no. 9 (September 3, 2012). See firstmonday.org.

4. This example is used in a template for creating Pareto charts in Excel. You can download the template from office.microsoft.com/en-us/templates/cost-analysis-with-pareto-chart-TC006082757.aspx.

5. Pareto charts are named for the Italian economist Vilfredo Pareto (1848–1923). Pareto was one of the first to analyze economic problems with mathematical tools. The Pareto Principle (sometimes called the 80/20 rule) takes various forms, such as “80% of the work is done by 20% of the people.” Pareto charts are a graphical version of the principle—the chart identifies the few important categories (the 20%) that account for most of the responses (the 80%). Of course, in any given setting, the actual percents will vary.

6. From the 2011 Canadian Census; see www12.statcan.ca/english/census.

7. Federal Reserve Bank of St. Louis; see research.stlouisfed.org/
fred2/series/WTB6MS.

8. Our eyes do respond to area, but not quite linearly. It appears that we perceive the ratio of two bars to be about the 0.7 power of the ratio of their actual areas. See W. S. Cleveland, The Elements of Graphing Data, Wadsworth, 1985, pp. 278–284.

9. Haipeng Shen, “Nonparametric regression for problems involving lognormal distributions,” PhD thesis, University of Pennsylvania, 2003. Thanks to Haipeng Shen and Larry Brown for sharing the data.

10. See Note 7.

11. U.S. Environmental Protection Agency, Municipal Solid Waste Generation, Recycling, and Disposal in the United States, Tables and Figures for 2012, February 2014.

12. May 2014 data from marketshare.hitslink.com.

13. See, for example, facebook.com/Million.Dollar.Application.

14. From socialbakers.com. The website says that the data are updated daily. These data were downloaded on June 15, 2014.

15. From the Bureau of Labor Statistics website, bls.gov.

16. From the 2011 Canadian Census; see statcan.gc.ca.

17. From the 2012 American Community Survey; see census.gov/acs/www/ and the U.S. Census web pages, census.gov/acs/www.

18. From the National Association of Home Builders website, nahb.org.

19. Rankings for 2013 from forbes.com/best-countries-for-business, downloaded June 17, 2014.

20. From the World Bank website, data.worldbank.org/data-catalog/GDP-ranking-table, updated May 8, 2014.

21. See Note 19.

22. From the Forbes website; see forbes.com/powerful-brands/.

23. From the Bureau of Labor Ststistics webpage, bls.gov/oes/2013/may/oes_nat.htm.

24. Downloaded from beer100.com/calories_in_beer.htm, on June 26, 2014.

25. Data for 2014 vehicles compiled by Natural Resources Canada; see nrcan.gc.ca/energy/efficiency/11938.

26. Information about the Indiana Statewide Testing for Educational Progress program can be found at doe.state.in.us/istep/.

27. Some software calls these graphs Normal probability plots. There is a technical distinction between the two types of graphs, but the terms are often used loosely.

28. The idea that all distributions are Normal in the middle is attributed to Charlie Winsor, See J. W. Tukey, A survey of sampling from contaminated distributions, in I. Olkin, S. G. Ghurye, W. Hoeffding, W. G. Madow, and H. B. Mann, eds., Contributions to Probability and Statistics, Essays in Honor of Harold Hotelling, Stanford University Press, 1960, pp. 448–485.

29. See stubhub.com.

30. From Matthias R. Mehl et al. “Are women really more talkative than men?” Science 317, no. 5834 (2007), p. 82.

31. Data from the careerbuilder.com website on July 3, 2014. See careerbuilder.com/jobs/keyword/business-administration.

32. See online.wsj.com/articles/the-world-rankings-of-flopping-1403660175.

33. From the World Bank website, see data.worldbank.org/
indicator/CM.MKT.LDOM.NO.

34. Color popularity from the 2012 Dupont Automotive Color Popularity Report, dupont.com/Media_Center/en_US/color_popularity/Images_2012/
Dupont_NAmerica_Color_Chart(HR).jpg.

1. Data for 2014 from usgovernmentspending.com/
compare_state_education_spend.

2. A sophisticated treatment of improvements and additions to scatterplots is W. S. Cleveland and R. McGill, “The many faces of a scatterplot,” Journal of the American Statistical Association, 79 (1984), pp. 807–822.

3. From the World Bank website, see data.worldbank.org/
indicator/CM.MKT.LDOM.NO.

4. See beer100.com.

5. See www12.statcan.ca.

6. See spectrumtechniques.com/isotope_generator.htm.

7. These data were collected under the supervision of Zach Grigsby, Science Express Coordinator, College of Science, Purdue University.

8. A careful study of this phenomenon is W. S. Cleveland, P. Diaconis, and R. McGill, “Variables on scatterplots look more highly correlated when the scales are increased,” Science 216 (1982), pp. 1138–1141.

9. From The Financial Development Report 2009, World Economic Forum, 2009; available from weforum.org.

10. From a presentation by Charles Knauf, Monroe County (New York) Environmental Health Laboratory.

11. Frank J. Anscombe, “Graphs in statistical analysis,” The American Statistician 27 (1973), pp. 17–21.

12. See target.com/site/en/corporate.

13. See, for example, niehs.nih.gov/health/topics/agents/emf, reviewed May 22, 2014.

14. C. M. Ryan, C. A. Northrup-Clewes, B. Knox, and D. I. Thurnham, “The effect of in-store music on consumer choice of wine,” Proceedings of the Nutrition Society 57 (1998), p. 1069A.

15. Education Indicators: An International Perspective, Institute of Education Studies, National Center for Education Statistics; see nces.ed.gov/surveys/international.

16. For an overview of remote deposit capture, see remotedepositcapture.com/overview/rdc.overview.aspx.

17. From the “Community Bank Competitiveness Survey,” 2008, ABA Banking Journal. The survey is available at nxtbook.com/nxtbooks/sb/ababj-compsurv08/index.php.

18. The counts reported were calculated using counts of the numbers of banks in the different regions and the percents given in the ABA report.

19. From M-Y Chen et al., “Adequate sleep among adolescents is positively associated with health status and health-related behaviors,” BMC Public Health, 6:59 (2006); available from biomedicalcentral.com/1471-2458/6/59.

20. See the U.S. Bureau of Census website at census.gov for these and similar data.

21. Based on The Ethics of American Youth—2012, available from the Josephson Institute at charactercounts.org/programs/reportcard/.

22. From the 2013–14 edition of the Purdue University Data Digest. See purdue.edu/datadigest.

23. From the 2012 Statistical Abstract of the United States, available at census.gov/compendia/statab/cats/population.html.

24. See Note 3.

25. OECD StatExtracts, Organization for Economic Cooperation Development, from stats.oecd.org/wbos.

26. Information about this procedure was provided by Samuel Flnigan of U.S. News & World Report. See usnews.com/usnews/rankguide/rghome.htm for a description of the variables used to construct the ranks and for the most recent ranks.

27. Based on data provided by Professor Michael Hunt and graduate student James Bateman of the Purdue University Department of Forestry and Natural Resources.

28. Reported in The New York Times, July 20, 1989, from an article appearing that day in the New England Journal of Medicine.

29. Condensed from D. R. Appleton, J. M. French, and M. P. J. Vanderpump, “Ignoring a covariate: An example of Simpson's paradox,” The American Statistician 50 (1996), pp. 340–341.

30. Lien-Ti Bei, “Consumers’ purchase behavior toward recycled products: An acquisition-transaction utility theory perspective,” MS thesis, Purdue University, 1993.

1. From bls.gov/spotlight/2013/ilc/pdf/international-labor-comparisons.pdf.

2. See, for example, mathsreports.wordpress.com/overall-narrative/mathematics-is-important/.

3. See nationsreportcard.gov/reading_math_2013/#/performance-overview.

4. See the NORC web pages at norc.uchicago.edu.

5. From caffeineinformer.com/the-15-top-energy-drink-brands.

6. From “Did you know,” Consumer Reports, February 2013, p. 10.

7. See, for example, oregonlive.com/today/index.ssf/2014/05/
national_exam_shows_us_12th-gr.html.

8. Based on a study conducted by Tammy Younts and directed by Professor Deb Bennett of the Purdue University Department of Educational Studies. For more information about Reading Recovery, see readingrecovery.org.

9. Based on a study conducted by Rajendra Chaini under the direction of Professor Bill Hoover of the Purdue University Department of Forestry and Natural Resources.

10. See the Harvard Business Review Blog Network entry, blogs.hbr.org/2013/04/the-hidden-biases-in-big-data.

11. See sm.rutgers.edu/pubs/Grinberg-SMPatterns-ICWSM2013.pdf.

12. From the Hot Ringtones list at billboard.com/ on July 26, 2014.

13. From the Top Heatseekers list at billboard.com/ on July 26, 2014.

14. From the online version of the Bureau of Labor Statistics, Handbook of Methods, at bls.gov. The details of the design are more complicated than the text describes.

15. The nonresponse rate for the CPS can be found at the Bureau of Labor Statistics website; see, for example, bls.gov/osmr/pdf/st100080.pdf. The GSS reports its response rate on its website, norc.org/projects/gensoc.asp.

16. The Pew Research Center for People and the Press designs careful surveys and is an execllent source of information about nonresponse. See pewresearch.org/about. See also, the Special Issue: Non-Response Bias in Household Surveys, Public Opinion Quarterly 70, no. 5 (2006).

17. See “Assessing the representativeness of public opinion surveys,” May 15, 2012, from people-press.org/2012/05/15.

18. From poll.gallup.com.

19. See nanpa.com/reports/area_code_relief_planning.html.

20. For a full description of the STAR program and its follow-up studies, go to heros-inc.org/star.htm.

21. Simplified from Arno J. Rethans, John L. Swasy, and Lawrence J. Marks, “Effects of television commercial repetition, receiver knowledge, and commercial length: A test of the two-factor model,” Journal of Marketing Research 23 (February 1986), pp. 50–61.

22. Based on an experiment performed by Jake Gandolph under the direction of Professor Lisa Mauer in the Purdue University Department of Food Science.

23. Based on an experiment performed by Evan Whalen under the direction of Professor Patrick Connolly in the Purdue University Department of Computer Graphics Technology.

24. Simplified from David L. Strayer, Frank A. Drews, and William A. Johnston, “Cell phone-induced failures of visual attention during simulated driving,” Journal of Experimental Psychology: Applied 9 (2003), pp. 23–32.

25. Based on a study conducted by Brent Ladd, a Water Quality Specialist with the Purdue University Department of Agricultural and Biological Engineering.

26. Based on a study conducted by Sandra Simonis under the direction of Professor Jon Harbor from the Purdue University Earth and Atmospheric Sciences Department.

27. John C. Bailar III, “The real threats to the integrity of science,” The Chronicle of Higher Education, April 21, 1995, pp. B1–B2.

28. See the details on the website of the Office for Human Research Protections of the Department of Health and Human Services, hhs.goc/ohrp.

29. The difficulties of interpreting guidelines for informed consent and for the work of institutional review boards in medical research are a main theme of Beverly Woodward, “Challenges to human subject protections in U.S. medical research,” Journal of the American Medical Association 282 (1999), pp. 1947–1952. The references in this paper point to other discussions. Updated regulations and guidelines appear on the OHRP website (see Note 2).

30. Quotation from the Report of the Tuskegee Syphilis Study Legacy Committee, May 20, 1996. A detailed history is James H. Jones, Bad Blood: The Tuskegee Syphilis Experiment, Free Press, 1993.

31. Dr. Hennekens’s words are from an interview in the Annenberg/Corporation for Public Broadcasting video series Against All Odds: Inside Statistics.

32. See ftc.gov/opa/2009/04/kellogg.shtm.

33. See findarticles.com/p/articles/mi_m0CYD/is_8_40/ai_n13675065/.

34. R. D. Middlemist, E. S. Knowles, and C. F. Matter, “Personal space invasions in the lavatory: Suggestive evidence for arousal,” Journal of Personality and Social Psychology 33 (1976), pp. 541–546.

35. For a review of domestic violence experiments, see C. D. Maxwell et al., The Effects of Arrest on Intimate Partner Violence: New Evidence from the Spouse Assault Replication Program, U.S. Department of Justice, NCH188199, 2001. Available online at ojp.usdoj.gov/nij/pubs-sum/188199.htm.

36. See the Federal Trade Commission website, ftc.gov, for more information about online behavioral advertising.

1. Closing price data are available from several sources, including finance.yahoo.com.

2. Color popularity for 2012 from the Dupont Automotive Color report; see dupont.com/Media_Center/en_US/color_popularity/2012_assets.html.

3. The full 2013 Canadian Medical Association report, 13th Annual National Report Card on Health Care, cma.ca.

4. Association of Certified Fraud Examiners, Report to the Nations on Occupational Fraud and Abuse 2014, acfe.com.

5. U.S. Department of Energy, Annual Energy Review 2011, see eia.gov/totalenergy/data/annual.

6. Results from 2011 survey by the Society for Human Resource Management; see shrm.org.

7. Results from 2013 study by Jude M. Werra & Associates, see judewerra.com/liars-index-.html.

8. 2013 Toronto Resident Casino Survey, conducted by Environics Research Group, toronto.ca.

9. The Gallup Organization, Confidence in Institutions, June 2013, gallup.com.

10. Based on 2011 census data from the website of Statistics Canada; see statcan.gc.ca.

11. Harris Poll, “Cyberchondriacs” on the Rise?, August 4, 2010, harrisinteractive.com.

12. Internet usage statistics, internetlivestats.com/internet-users.

13. Canadian transportation statistics from Statistics Canada, statcan.gc.ca. U.S. transportation statistics from U.S. Bureau of Transportation Statistics, bts.gov.

14. See Note 2.

15. From the website of the Bureau of Labor Statistics, bls.gov.

16. M. Ozanian, “The most valuable NFL teams.” From the SportsMoney section of Forbes online, forbes.com/sportsmoney, August 14, 2013.

17. Estimated probabilities from the National Collegiate Athletic Association (NCAA); see ncaa.org. Note: The NCAA reports that 1.6% of college seniors are drafted into the NFL. Our use of 1.2% accounts for the attrition of some college players who never make it to their senior year.

18. See Note 17.

19. W. D. Witnauer, R. G. Rogers, and J. M. Saint Onge, “Major league baseball career length in the 20th Century,” Population Research and Policy Review 26 (2007), pp. 371–386.

20. From the Fitch Ratings Global Corporate Finance 2013 Transition and Default Study, fitchratings.com.

21. From IRS Tax Statistics; see irs.gov/uac/Tax-Stats-2.

22. We use both for the random variable, which takes different values in repeated sampling, and for the numerical value of the random variable in a particular sample. Similarly, stands both for a random variable and for a specific value. This notation is mathematically imprecise but statistically convenient.

23. Based on L. Alwan, M. Xu, D. Yao, and X. Yue, “The Dynamic Newsvendor Model with Correlated Demand,” (January 9, 2015), available online at Social Science Research Network, ssrn.com/abstract=2547424.

24. The mean of a continuous random variable with density function can be found by integration:

This integral is a kind of weighted average, analogous to the discrete-case mean

The variance of a continuous random variable is the average squared deviation of the values of from their mean, found by the integral

25. See A. Tversky and D. Kahneman, “Belief in the law of small numbers,” Psychological Bulletin 76 (1971), pp. 105–110; and other writings of these authors for a full account of our misperception of randomness.

26. Probabilities involving runs can be quite difficult to compute. That the probability of a run of three or more heads in 10 independent tosses of a fair coin is can be found by clever counting, as can the other results given in the text. A general treatment using advanced methods appears in Section XIII.7 of William Feller, An Introduction to Probability Theory and Its Applications, Vol. 1, 3rd ed., Wiley, 1968.

27. R. Vallone and A. Tversky, “The hot hand in basketball: On the misperception of random sequences,” Cognitive Psychology 17 (1985), pp. 295–314. A later series of articles that debate the independence question is A. Tversky and T. Gilovich, “The cold facts about the ‘hot hand’ in basketball,” Chance 2, no. 1 (1989), pp. 16–21; P. D. Larkey, R. A. Smith, and J. B. Kadane, “It’s OK to believe in the ‘hot hand,"’ Chance 2, no. 4 (1989), pp. 22–30; and A. Tversky and T. Gilovich, “The ‘hot hand’: Statistical reality or cognitive illusion?” Chance 2, no. 4 (1989), pp. 31–34.

28. As an example, the Charles Schwab’s website (www.schwab.com) provides mean returns and standard deviations of returns for all its managed mutual funds under Investment Help.

29. See Note 1.

30. See Note 1.

31. From the 2012 Statistical Abstract of the United States, Table 299.

32. Ibid., Table 278.

1. More details on importance of marketing research at Procter & Gamble can be found at pg.com/en_US/company/core_strengths.shtml.

2. Results from 2013 University of Southern California Annenberg School for Communication and Journalism World Internet Project report, digitalcenter.org.

3. S. A. Rahimtoola, “Outcomes 15 years after valve replacement with a mechanical vs. a prosthetic valve: Final report of the Veterans Administration randomized trial,” Journal of American College of Cardiology 36 (2000), pp. 1152–1158.

4. J. J. Koehler and C. A. Conley, “The hot hand myth in professional basketball,” Journal of Sport and Exercise Psychology 25 (2003), pp. 253–259.

5. From gallup.com on June 23, 2014.

6. From Bank of America Trends in Consumer Mobility Report 2014, newsroom.bankofamerica.com.

7. A description and summary of this 2012 survey can be found at ipsos-na.com.

8. Results reported at Philadelphia Mayor’s Office of Transportation & Utilities, phillymotu.wordpress.com.

9. Barbara Means et al., “Evaluation of evidence-based practices in online learning: A meta-analysis and review of online learning studies,” U.S. Department of Education, Office of Planning, Evaluation, and Policy Development, 2010.

10. A summary of Larry Wright’s study can be found at nytimes.com/2009/03/04/sports/basketball/04freethrow.html.

11. Findings are from the Time Mobility Poll run between June 29 and July 28, 2012. The results were published in the August 27, 2012, issue of Time.

12. Data from football-data.co.uk/englandm.php.

13. Data provided by Professor Maria Goranova of the University of Wisconsin-Milwaukee.

14. B. D. Bowen and D. E. Headley, Airline Quality Rating 2014, commons.erau.edu/aqrr/1.

15. From thefuturecompany.com, January 29, 2013.

16. Harassment survey from aauw.org reported on January 30, 2013.

1. K. M. Orzech et al., “The state of sleep among college students at a large public university,” Journal of American College Health 59 (2011), pp. 612–619.

2. The description of the 2011 survey and results obtained from blog.appsfire.com.

3. From the website of the U.S. Bureau of Transportation Statistics, rita.dot.gov/bts/.

4. Findings are from Nielson’s “State of the Appnation— a year of change and growth in U.S. Smart-phones,” posted May 16, 2012, blog.nielson.com/nielsonwire/.

5. Statistics regarding Facebook usage can be found at facebook.com/notes/facebook-data-team/anatomy-of-facebook/10150388519243859.

6. From the grade distribution database of the Indiana University Office of the Registrar, gradedistribution.registrar.indiana.edu.

7. The 2010–2011 statistics for California were obtained from the California Department of Education website, dq.cde.ca.gov.

8. Based on information reported in “How America pays for college 2012,” news.salliemae.com.

9. See Note 8. This total amount includes grants, scholarships, loans, and assistance from friends and family.

10. Average starting salary taken from the Class of 2013 salary survey by the National Association of Colleges and Employers, naceweb.org.

11. See thekaraokechannel.com/online#.

12. Average starting salaries for different business majors for students from University of Texas at Austin are found at mccombs.utexas.edu/Career-Services/Statistics.

13. The vehicle is a 2006 Toyota Highlander Hybrid.

14. Data obtained from the Philippine Statistics Authority, census.gov.ph.

15. Information reported in “State of American well-being: 2013 state, community, and congressional district analysis,” at info.healthways.com/wellbeingindex.

16. S. Song, J. Tan, and Y. Yi, “IPO initial returns in China: Underpricing or overvaluation?,” China Journal of Accounting Research 7 (2014), pp. 31–49.

17. Anahad O’Connor, “Herbal supplements are often not what they seem,” New York Times, November 3, 2013.

18. From a study by M. R. Schlatter et al., Division of Financial Aid Purdue University.

19. L. Bauld, K. Angus, and M. de Andrade, “E-cigarette uptake and marketing,” 2014 report commissioned by Public Health England.

20. R. A. Fisher, “The arrangement of field experiments,” Journal of the Ministry of Agriculture of Great Britain 33 (1926), p. 504, quoted in Leonard J. Savage, “On rereading R. A. Fisher,” Annals of Statistics 4 (1976), p. 471. Fisher’s work is described in a biography by his daughter: Joan Fisher Box, R. A. Fisher: The Life of a Scientist, Wiley, 1978.

21. Warren E. Leary, “Cell phones: Questions but no answers,” New York Times, October 26, 1999.

22. Reported by Jon Hamilton, “Big-box stores’ hurricane prep starts early,” National Public Radio, August 26, 2011; story transcript found at npr.org/2011/08/26/139941596/big-box-stores-hurricane-prep-starts-early.

23. A. Zibel and K. Hudson, “Surveys show shrinking ranks of uninsured,” Wall Street Journal, July 20, 2014.

24. D. Bakotic, “Job satisfaction and employees’ individual characteristics,” Journal of American Academy of Business 20 (2014), pp. 135–140.

25. B. Gillai et al., “The relationship between responsible supply chain practices and performance,” Insights from the Stanford Initiative for the Study of Supply Chain Responsibility (SISSCR), November 2013.

26. Data provided by Mugdha Gore and Joseph Thomas, Purdue University School of Pharmacy.

1. Information from the “Mobile Life” 2013 report can be found at news.o2.co.uk/?press-release=i-cant-talk-dear-im-on-my-phone.

2. From C. Don Wiggins, “The legal perils of ‘underdiversification’—a case study,” Personal Financial Planning 1, no. 6 (1999), pp. 16–18.

3. Data provided by Bill Berezowitz and James Malloy of GE Healthcare.

4. Go to futurity.org/fried-food-taste-without-all-the-fat/ for more information.

5. These recommendations are based on extensive computer work. See, for example, Harry O. Posten, “The robustness of the one-sample t -test over the Pearson system,” Journal of Statistical Computation and Simulation 9 (1979), pp. 133–149; and E. S. Pearson and N. W. Please, “Relation between the shape of population distribution and the robustness of four simple test statistics,” Biometrika 62 (1975), pp. 223–241.

6. The standard reference here is Bradley Efron and Robert J. Tibshirani, An Introduction to the Bootstrap, Chapman Hall, 1993. A less technical overview is in Bradley Efron and Robert J. Tibshirani, “Statistical data analysis in the computer age,” Science 253 (1991), pp. 390–395.

7. From “Insolvency Statistics in Canada 2013—Annual report” available at ic.gc.ca/eic/site/bsf-osb.nsf/eng/br03221.html.

8. This announcement can be found at epa.gov/fueleconomy/labelchange.htm.

9. Niels van de Ven et al., “The return trip effect: Why the return trip often seems to take less time,” Psychonomic Bulletin and Review 18, no. 5 (2011), pp. 827–832.

10. From the 2012 Annual Report on consumer expenditures released in May 2014 and found at bls.gov/cex/#tables.

11. Data from Ray Weaver and Shane Frederick, “A reference price theory of the endowment effect,” Journal of Marketing Research 49 (October 2012), pp. 696–707.

12. A description of the lawsuit can be found at cnn.com/2013/02/26/business/california-anheuser-busch-lawsuit/index.html.

13. Results from the April 2011 report titled “National Health Care and Discharged Hospice Care Patients” available at cdc.gov/nchs/products/nhsr.htm.

14. Based on 2013 information from the USDA Feed Grains Database available at ers.usda.gov.

15. Data provided by Joseph A. Wipf, Department of Foreign Languages and Literatures, Purdue University.

16. Christine L. Porath and Amir Erez, “Overlooked but not untouched: How rudeness reduces onlookers’ performance on routine and creative tasks,” Organizational Behavior and Human Decision Processes 109 (2009), pp. 29–44.

17. Data provided by Timothy Sturm.

18. The Satterthwaite degrees of freedom are given by

This distribution approximation is quite accurate when both sample sizes and are 5 or larger.

19. Detailed information about the conservative procedures can be found in Paul Leaverton and John J. Birch, “Small sample power curves for the two sample location problem,” Technometrics 11 (1969), pp. 299–307; Henry Scheffé, “Practical solutions of the Behrens-Fisher problem,” Journal of the American Statistical Association 65 (1970), pp. 1501–1508; and D. J. Best and J. C. W. Rayner, “Welch’s approximate solution for the Behrens-Fisher problem,” Technometrics 29 (1987), pp. 205–210.

20. Koert van Ittersum et al., “Smart shopping carts: How real-time feedback influences spending,” Journal of Marketing 77 (November 2013), pp. 21–36.

21. Extensive simulation studies are reported in Harry O. Posten, “The robustness of the two-sample test over the Pearson system,” Journal of Statistical Computation and Simulation 6 (1978), pp. 295–311; Harry O. Posten, H. Yeh, and D. B. Owen, “Robustness of the two-sample t-test under violations of the homogeneity assumption,” Communications in Statistics 11 (1982), pp. 109–126; and Harry O. Posten, “Robustness of the two-sample t-test under violations of the homogeneity assumption, part II,” Journal of Statistical Computation and Simulation 8 (1992), pp. 2169–2184.

22. Based on information made available June 2014 titled “Wheat Data: Yearbook Tables: Wheat: Average price received by farmers, United States,” available at ers.usda.gov/data-products/wheat-data.aspx#.U7LgyihCz_c.

23. Based on Mary H. Keener, “Predicting the financial failure of retail companies in the United States,” Journal of Business & Economic Research 11, no. 8 (2013), pp. 373–380.

24. Aron Levin et al., “Ad nauseam? Sports fans’ acceptance of commercial messages during televised sporting events,” Sport Marketing Quarterly 22 (2013), pp. 193–202.

25. Karel Kleisner et al., “Trustworthy-looking face meets brown eyes,” PLoS ONE 8, no. 1 (2013), e53285, doi:10.1371/journal.pone.0053285.

26. Cynthia E. Cryfer et al., “Misery is not miserly: Sad and self-focused individuals spend more,” Psychological Science 19 (2008), pp. 525–530.

27. Elizabeth F Beach and Valerie Nie, “Noise levels in fitness classes are still too high: Evidence from 19971998 and 2009–2011,” Archives of Environmental & Occupational Health 69, no. 4 (2014), pp. 223–230.

28. The 2013 study can be found at qsrmagazine.com/content/drive-thru-performance-study-customer-service.

29. B. Bakke et al., “Cumulative exposure to dust and gases as determinants of lung function decline in tunnel construction workers,” Occupational Environmental Medicine 61 (2004), pp. 262–269.

30. Y. Charles Zhang and Norbert Schwarz, “How and why 1 year differs from 365 days: A conversational logic analysis of inferences from the granularity of quantitative expressions,” Journal of Consumer Research 39 (August 2012), pp. S212–S223.

31. Based on A. H. Ismail and R. J. Young,"The effect of chronic exercise on the personality of middle-aged men,” Journal of Human Ergology 2 (1973), pp. 47–57.

32. The average starting salary taken from a 2014 summer salary survey by the National Association of Colleges and Employers (NACE).

33. 2014 press release from The Student Monitor available at studentmonitor.com.

34. This city’s restaurant inspection data can be found at jsonline.com/watchdog/dataondemand/.

35. B. Wansink et al., “Fine as North Dakota wine: Sensory expectations and the intake of companion foods,” Physiology & Behavior 90 (2007), pp. 712–716.

36. P. Glick et al., “Evaluations of sexy women in low-and high-status jobs,” Psychology of Women Quarterly 29 (2005), pp. 389–395.

37. Morgan K. Ward and Darren W. Dahl, “Should the devil sell Prada? Retail rejection increases aspiring consumers’ desire for the brand,” Journal of Consumer Research 41, no. 3 (2014), pp. 590–609.

38. Ajay Ghei, “An empirical analysis of psychological androgeny in the personality profile of the successful hotel manager,” MS thesis, Purdue University, 1992.

39. Data from the “wine” database in the archive of machine learning data bases at the University of California, Irvine, ftp.ics.uci.edu/pub/machine-learning-databases.

40. Kiju Jung et al., “Female hurricanes are deadlier than male hurricanes,” Proceedings of the National Academy of Sciences 111, no. 24 (2014), pp. 8782–8787.

41. Yvan R. Germain, “The dyeing of ramie with fiber reactive dyes using the cold pad-batch method,” MS thesis, Purdue University, 1988.

42. Refer to the previous note.

43. This exercise is based on events that are real. The data and details have been altered to protect the privacy of the individuals involved.

44. G. E. Smith et al., “A cognitive training program based on principles of brain plasticity: Results from the improvement in memory with plasticity-based adaptive cognitive training (IMPACT) study,” Journal of the American Geriatrics Society epub (2009), pp. 1–10.

45. Based on G. Salvendy, “Selection of industrial operators: The one-hole test,” International Journal of Production Research 13 (1973), pp. 303–321.

1. See the PriceWaterhouseCoopers website, pwc.com.

2. From pewinternet.org/2014/08/06/future-of-jobs.

3. For more information about the survey, see aba.com/Products/Surveys/
Pages/2013BankInsuranceSurveyReport.aspx.

4. See A. Agresti and B. A. Coull, “Approximate is better than ‘exact’ for interval estimation of binomial proportions,” The American Statistician 52 (1998), pp. 119–126. A detailed theoretical study is Lawrence D. Brown, Tony Cai, and Anirban DasGupta, “Confidence intervals for a binomial proportion and asymptotic expansions,” Annals of Statistics 30 (2002), pp. 160–201.

5. This example is adapted from a survey directed by Professor Joseph N. Uhl of the Department of Agricultural Economics, Purdue University. The survey was sponsored by the Indiana Christmas Tree Growers Association.

6. Results of the survey are available at slideshare.net/duckofdoom/google-research-about-mobile-internet-in-2011.

7. See southerncross.co.nz/about-the-group/media-releases/2013.aspx.

8. A report on this poll was posted on the Gallup website on June 23, 2014. See gallup.com/poll/171785/americans-say-social-media-little-effect-buying-decisions.aspx.

9. Reported online on March 6, 2012, at ipsos-na.com/news-polls/pressrelease.aspx?id=5537.

10. Heather Tait, Aboriginal Peoples Survey, 2006: Inuit Health and Social Conditions (2008), Social and Aboriginal Statistics Division, Statistics Canada. Available from statcan.gc.ca/pub.

11. See news.teamxbox.com/xbox/18254.

12. From the “National Survey of Student Engagement, The College Student Report 2014,” available online at nsse.iub.edu.

13. Oliver Meixner et al., “The use of social media within the Austrian supply chain for food and beverages,” Proceedings in System Dynamics and Innovations in Food Networks (2013), pp. 1–13. See centmapress.ilb.uni-bonn.de/ojs/index.php/
proceedings/index.

14. See Alan Agresti and Brian Caffo, “Simple and effective confidence intervals for proportions and differences of proportions result from adding two successes and two failures,” The American Statistician 45 (2000), pp. 280–288. The Wilson interval is a bit conservative (true coverage probability is higher than the confidence level) when and are equal and close to 0 or 1, but the traditional interval is much less accurate and has the fatal flaw that the true coverage probability is less than the confidence level.

15. Nicolas Gueguen and Celine Jacob, “Clothing color and tipping: Gentlemen patrons give more tips to waitresses with red clothes,” Journal of Hospitality & Tourism Research 38, no. 2 (2014), pp. 275–280.

16. See S. W. Lagakos, B. J. Wessen, and M. Zelen, “An analysis of contaminated well water and health effects in Woburn, Massachusetts,” Journal of the American Statistical Association 81 (1986), pp. 583–596, and the following discussion. This case is the basis for the movie A Civil Action.

17. See, for example, gartner.com/it-glossary/internet-of-things.

18. From pewinternet.org/2014/05/14/internet-of-things, posted May 14, 2014.

19. Reported in Stephanie Goldberg, “Benefits integration picks up steam; compliance drives interest in combining workplace absence programs,” Business Insurance 48, no. 17 (2014), p. 14. Also, see the “2014 Aon Newitt Health Care Survey” at aon.com.

20. Jiao Xu et al., “News media channels: Complements or substitutes? Evidence from mobile phone usage,” Journal of Marketing 78 (2014), pp. 97–112. The methodology used in the study has been simplified for our purposes.

21. From Rick B. van Baaren, “The parrot effect: How to increase tip size,” Cornell Hotel and Restaurant Administration Quarterly 46 (2005), pp. 79–84.

22. Some details are given in D. H. Kaye and M. Aickin (eds.), Statistical Methods in Discrimination Litigation, Marcel Dekker, 1986.

23. The report, dated May 18, 2012, is available from pewinternet.org/Reports/2012/Future-of-Gamification/Overview.aspx.

24. From the Pew Research Center’s Project for Excellence in Journalism, The State of the News Media 2012, available from stateofthemedia.org/?src=prc-headline.

25. Data are from the NOAA Satellite and Information Service at ncdc.noaa.gov/special-reports/groundhog-day.php.

1. Oliver Meixner et al., “The use of social media within the Austrian supply chain for food and beverages,” Proceedings in System Dynamics and Innovations in Food Networks (2013), pp. 1–13. See centmapress.ilb.uni-bonn.de/ojs/index.php/proceedings/index.

2. Marek Matejun, “The role of flexibility in building the competitiveness of small and medium enterprises,” Management 18, no. 1 (2014), pp. 154–168.

3. When the expected cell counts are small, it is best to use a test based on the exact distribution rather than the chi-square approximation, particularly for tables. Many statistical software systems offer an “exact” test as well as the chi-square test for tables.

4. The full report of the study appeared in George H. Beaton et al., “Effectiveness of vitamin A supplementation in the control of young child morbidity and mortality in developing countries,” United Nations ACC/SCN State-of-the-Art Series, Nutrition Policy Discussion Paper no. 13, 1993.

5. The sampling procedure was designed by George McCabe. It was carried out by Amy Conklin, an undergraduate honors student in the Department of Foods and Nutrition at Purdue University.

6. The analysis could also be performed by using a two-way table to compare the states of the selected and not-selected students. Because the selected students are a relatively small percent of the total sample, the results will be approximately the same.

7. See the M&M Mars website at us.mms.com/us/about/products for this and other information.

8. Nicolas Gueguen an Celine Jacob, “Clothing color and tipping: Gentlemen patrons give more tips to waitresses with red clothes,” Journal of Hospitality & Tourism Research 38, no. 2 (2014), pp. 275–280.

9. Based on Shan Feng et al., “Does classical music relieve math anxiety? Role of tempo on price computational avoidance,” Psychology & Marketing 31, no. 7 (2014) pp. 489–499.

10. From Theo Lieven et al., “The effect of brand gender on brand equity,” Psychology & Marketing 31, no. 5 (2014) pp. 371–385.

11. Based on pewsocialtrends.org/files/2011/08/online-learning.pdf.

12. For an overview of remote deposit capture, see remotedepositcapture.com/overview/rdc.overview.aspx.

13. From the “Community Bank Competitiveness Survey,” 2008, ABA Banking Journal. The survey is available at nxtbook.com/nxtbooks/sb/ababj-compsurv08/index.php.

14. The marginal percent of yes responses in this table does not agree with the corresponding percent from the table in the previous exercise. The counts reported in this exercise were calculated using counts of the numbers of banks in the different regions and the percents given in the ABA report. The percents match the figures given in the 2012 report.

15. Based on The Ethics of American Youth: 2012, available from the Josephson Institute, charactercounts.org/programs/reportcard/.

16. See pewinternet.org/about.asp.

17. Data are from the report Home Broadband Adoption 2013 which was prepared by the Pew Internet American Life Project. See pewinternet.org/2013/08/26/home-broadband-2013.

18. See nhcaa.org.

19. These data are a composite based on several actual audits of this type.

20. From the National Survey of Student Engagement, 2014 Results; available from nsse.iub.edu.

21. From Robert J. M. Dawson, “The ‘unusual episode’ data revisited,” Journal of Statistics Education 3, no. 3 (1995). Electronic journal available at the American Statistical Association website, amstat.org.

1. In practice, may also be a random quantity. Inferences can then be interpreted as conditional on a given value of .

2. M. Van Praag et al., “The higher returns to formal education for entrepreneurs versus employees,” Small Business Economics 40 (2013), pp. 375–396.

3. National Science Foundation, National Center for Science and Engineering Statistics, Higher Education Research and Development: Fiscal Year 2013. Detailed tables released in February 2015 and available at nsf.gov/statistics/nsf13325/.

4. As the text notes, the residuals are not independent observations. They also have somewhat different standard deviations. For practical purposes of examining a regression model, we can nonetheless interpret the Normal quantile plot as if the residuals were data from a single distribution.

5. Inflation is measured by the December-to-December change in the Consumer Price Index. These data were found at bls.gov/cpi/. Interest rates for the six-month secondary market Treasury bill were obtained at federalreserve.gov/releases/h15/data.htm.

6. See the essay “Regression toward the mean,” in Stephen M. Stigler, Statistics on the Table, Harvard University Press, 1999. The quotation from Milton Friedman appears in this essay.

7. In fact, the Excel regression output does not report the sign of the correlation . The scatterplot in Figure 10.3 shows that is positive. To get the correlation with the correct sign in Excel, you must use the “Correlation” function.

8. Selling price and assessment value available at php.jconline.com/propertysales/propertysales.php.

9. Tuition and fees for 2008 and tuition for 2013 were obtained from findthebest.com. Tuition rates for 2000 from the “2000–2001 Tuition and Required Fees Report,” University of Missouri.

10. M. Plotnicki and A. Szyszka, “IPO market timing. The evidence of the disposition effect among corporate managers,” Global Finance Journal 25 (2014), pp. 48–55.

11. M. Mondello and J. Maxcy, “The impact of salary dispersion and performance bonuses in NFL organizations,” Management Decision 47 (2009), pp. 110–123. These data were collected from cbssports.com/nfl/playerrankings/regularseason/ and content.usatoday.com/sports/football/nfl/salaries/.

12. Z. Xuan et al., “Tax policy, adult binge drinking, and youth alcohol consumption in the United States,” Alcoholism: Clinical and Experimental Research 37, no. 10 (2013), pp. 1713–1719.

13. Data on net new cash flow of long-term mutual funds obtained from Chapter 2: Recent Mutual Fund Trends, 2014 Investment Company Company Fact Book, Investment Company Institute, icifactbook.org/.

14. Data were provided by the Ames City Assessor, Ames, Iowa.

15. These are part of the data from the EESEE story “Blood Alcohol Content,” found on the text website.

16. Data sampled from jcmit.com/memoryprice.htm.

17. Data on fuel consumption ratings made available by the Government of Canada, data.gc.ca/data/en/dataset/98f1a129-f628-4ce4-b24d-6f16bf24dd64.

18. Based on summaries in Charles Fombrun and Mark Shanley, “What’s in a name? Reputation building and corporate strategy,” Academy of Management Journal 33 (1990), pp. 233–258.

19. This annual report can be found at kiplinger.com.

20. Data available at ncdc.noaa.gov.

21. W. G. Kim and H–B. Kim, “Measuring customer-based restaurant brand equity,” Cornell Hotel and Restuarant Administration Quarterly 45, no. 2 (2004), pp. 115–131.

22. S. Groschl, “Persons with disabilities, A source of nontraditional labor for Canada’s hotel industry,” Cornell Hotel and Restuarant Administration Quarterly 46, no. 2 (2005), pp. 258–274.

23. From the Supermarket Facts web page of the Food Marketing Institute located at fmi.org.

24. Table of values available at ers.usda.gov/Data/AgProductivity/.

1. Based on the 2007 Space Management Model for Purdue University implemented by Keith Murray, Director of Space Management and Academic Scheduling.

2. The BBC Global 30 is a global stock market index that mixes economic information from the world’s largest companies. It was started by the BBC in 2004. These data were obtained online from Yahoo! Finance.

3. U.S. Federal Deposit Insurance Corp., Statistics on Banking, issued annually. Information for current year can be found online at www2.fdic.gov/SDI/SOB/.

4. E. Wong et al., “A face only an investor could love: CEOs’ facial structure predicts their firms’ financial performance,” Psychological Science 22, no. 12 (2011), pp. 1478–1483.

5. T. Almunais et al., “Determinants of accounting students performance,” Business Education & Accreditation 6, no. 2 (2014), pp. 1–9.

6. Available at ConsumerReports.org. Latest summary posted December 2014.

7. These data were obtained from “The QSR 50,” an annual report provided by QSR magazine, qsrmagazine.com/reports.

8. Data provided by the owners of Duck Worth Wearing, Ames, Iowa.

9. From a table entitled “Largest Indianapolis-area architectural firms,” Indianapolis Business Journal, June 15, 2014.

10. The data were obtained from the Internet Movie Database (IMDb), imdb.com, on August 14, 2014.

11. The KISS principle refers to the empirical principle “Keep it simple, stupid.” In regression, this refers to keeping the models simple and avoiding unnecessary complexity.

12. Katharine Kelley et al., “Estimating consumer spending on tickets, merchandise, and food and beverage: A case study of a NHL team,” Journal of Sport Management 28 (2014), pp. 253–265.

13. From Michael E. Staten et al., “Information costs and the organization of credit markets: A theory of indirect lending,” Economic Inquiry 28 (1990), pp. 508–529.

14. The summary information taken from “FINAL REPORT: Canada Small Business Financing Program (CSBFP) Awareness and Satisfaction Study,” prepared for Industry Canada by R.A. Malatest & Associates Ltd., July 2013.

15. From Susan Stites-Doe and James J. Cordeiro, “An empirical assessment of the determinants of bank branch manager compensation,” Journal of Applied Business Research 15 (1999), pp. 55–66.

16. The data were collected from realtor.com on October 8, 2001.

17. Tom Reichert, “The prevalence of sexual imagery in ads targeted to young adults,” Journal of Consumer Affairs 37 (2003), pp. 403–412.

18. For more information on logistic regression see Chapter 17S.

19. Bill Merrilees and Tino Fenech, “From catalog to Web: B2B multi-channel marketing strategy,” Industrial Marketing Management 36 (2007), pp. 44–49.

20. Based on M. U. Kalwani and C. K. Yim, “Consumer price and promotion expectations: An experimental study,” Journal of Marketing Research 29 (1992), pp. 90–100.

21. Tung-Shan Liao and John Rice, “Innovation investments, market engagement and financial performance: A study among Australian manufacturing SMEs,” Research Policy 39, no. 1 (2010), pp. 117–125.

22. R. East et al., “Measuring the impact of positive and negative word of mouth on brand purchase probability,” International Journal of Research in Marketing 25 (2008), pp. 215–224.

23. Yield data can be obtained at nass.usda.gov/Quick_Stats.

24. A description of this case, as well as other examples of the use of statistics in legal settings, is given in Michael O. Finkelstein, Quantitative Methods in Law, Free Press, 1978.

1. As of 2015, the American Society for Quality (ASQ) has honored 26 individuals by conferring on them the status of Honorary Member. A detailed summary of the background and contributions of the individuals noted here along with other pioneers can be found from an ASQ website, asq.org/about-asq/who-we-are/honorary-members.html.

2. The cause-and-effect diagram was prepared by S. K. Bhat of the General Motors Technical Center as part of a course assignment at Purdue University.

3. Control charts were invented in the 1920s by Walter Shewhart at the Bell Telephone Laboratories. Shewhart’s classic book, Economic Control of Quality of Manufactured Product (Van Nostrand, 1931), organized the application of statistics to improving quality.

4. In his classic book, Out of the Crisis (MIT Center for Advanced Engineering Study, 1986), W. Edwards Deming demonstrates the effects of counterproductive adjustment to an in-control process by means of a physical experiment based on dropping marbles through a funnel onto a tabletop. Participants in the experiment learn that the least scatter on the table-top is obtained by not moving the funnel, that is, by means of “no action.”

5. In statistics, the term “efficient” relates to the variance of the sampling distribution of the estimator. The estimator with the smallest variation is referred to as an efficient estimator.

6. Simulated data based on information appearing inn Arvind Salvekar, “Application of six sigma to DRG 209,” found at the Smarter Solutions website, smartersolutions.com.

7. Game log statistics on NBA players can be found at stats.nba.com.

8. The exact formula for is given by

where is the number of observations and, if the argument of the factorial is a non-integer, it is computed as follows:

9. Data provided by Linda McCabe, Purdue University.

10. Data provided by Colleen O’Brien, Team Leader Quality Resource and Privacy and Safety Officer, Bellin Health.

11. Data on aviation accidents can be found at the Federal Aviation Administration (FAA) Data & Research page, faa.gov/data_research/.

1. Michael Siconolfi, “Walgreen shakeup followed bad projection,” Wall Street Journal, August 19, 2014.

2. Stock prices (including those for Disney) can be found at finance.yahoo.com.

3. Amazon quarterly net sales data were extracted from quarterly reports found by following the link “Investor Relations” at amazon.com.

4. The differences in correlation values are due to the fact that the ACF computes the correlations by using the same sample mean for the variable and the lag variable , namely, the sample of the whole series. The variable has observations, while the has observations. Standard correlation formula would treat these variables different and thus use two different sample means.

5. See Note 2.

6. Data available from the Economic Research website of the Federal Reserve Bank of St. Louis, research.stlouisfed.org.

7. Data from the Thomson Reuters/University of Michigan Consumers of Surveys website, sca.isr.umich.edu.

8. A variety of historical data on gold can be found at the World Gold Council website, gold.org.

9. See Note 6.

10. Data provided by David Robinson.

11. Data were extracted from quarterly reports from the investor relations website of LinkedIn, investors.linkedin.com.

12. Data from the National Bureau of Statistics of China website, stats.gov.cn/english.

13. Data extracted from the International Telecommunication Union (United Nations specialized agency), itu.int.

14. Data extracted using the data tools found at the U.S. Census Bureau, census.gov.

15. For more details on the issues associated with log transformation in regression see D. Miller, “Reducing transformation bias in curve fitting,” The American Statistician 38 (1984), pp. 124–126.

16. See Note 6.

17. Data found at the statistics portal (statista.com); original source is the hotel data tracking company STR, str.com.

18. See Note 6.

19. Data from the Canadian Tourism Commission website, en-corporate.canada.travel.

20. Data were extracted from quarterly reports extracted from quarterly reports found by following the link “Investor Relations” at att.com.

21. There are many excellent books on ARIMA modeling, including the authoritative reference book of G. E. P. Box, G. M. Jenkins, and G. C. Reinsel, Time Series Analysis: Forecasting and Control, 4th ed., Wiley, 2008.

22. Data obtained from the National Oceanic and Atmospheric Administration Great Lakes Environmental Research Laboratory, glerl.noaa.gov.

23. Data obtained from the U.S. Bureau Labor of Statistics, bls.gov.

24. Data obtained from the baseball statistics website, baseball-reference.com.

25. Data obtained from OPEC website, opec.org.

26. Data obtained from American Public Transportation Association website, apta.com.

27. See Note 6.

28. See Note 6.

29. The exponential smoothing model is the forecasting equation for an ARIMA(0, 1, 1) model. See reference given in Note 21.

30. Data obtained from the Bureau of Transportation Statistics, bts.gov.

31. Data were extracted from quarterly reports found by following the link “Investor Relations” at hrblock.com.

32. See Note 6.

33. Data were obtained from the City of Chicago data portal, data.cityofchicago.org.

34. Data available from the Economic Research Service website of the U.S. Department of Agriculture, ers.usda.gov.

35. Data available from the Office of the New Jersey State Climatologist website at Rutgers University, climate.rutgers.edu/stateclim.

36. Data obtained from the NFL statistics website, pro-football-reference.com.

37. Densities of populations over time of most countries in the world can be found at the World Bank website, worldbank.org.

38. Data found at the statistics portal, statista.com.

39. See Note 14.

40. See Note 30.

1. Based on A. Bhattacharjee et al., “Tip of the hat, wag of the finger: How moral decoupling enables consumers to admire and admonish,” Journal of Consumer Research 39, no. 6 (2013), pp. 1167–1184.

2. This rule is intended to provide a general guideline for deciding when serious errors may result by applying ANOVA procedures. When the sample sizes in each group are very small, this rule may be a little too conservative. For unequal sample sizes, particular difficulties can arise when a relatively small sample size is associated with a population having a relatively large standard deviation.

3. Penny M. Simpson et al., “The eyes have it, or do they? The effects of model eye color and eye gaze on consumer ad response,” Journal of Applied Business and Economics 8 (2008), pp. 60–71.

4. Discussion on this and other tests can be found in M.H. Kutner et al., Applied Linear Models, 5th ed., McGraw-Hill/Irwin, 2005.

5. This example is based on data from a study conducted by Jim Baumann and Leah Jones of the Purdue University School of Education.

6. Several different definitions for the noncentrality parameter of the noncentral distribution are in use. When , the defined here is equal to the square of the noncentrality parameter that we used for the two-sample test in Chapter 7. Many authors prefer . We have chosen to use because it is the form needed for the SAS function PROBF.

7. B. E. Saelens et al., “Relation between higher physical activity and public transit use,” American Journal of Public Health 104, no. 5 (2014), pp. 854–859.

8. F. Madhumita, “A study of changes to the Websites of British Columbia wineries between 2004 and 2012,” MS Dissertation (2013), University of British Colombia.

9. Kendall J. Eskine, “Wholesome foods and wholesome morals? Organic foods reduce prosocial behavior and harshen moral judgments,” Social Psychological and Personality Science, 2012, doi: 10.1177/1948550612447114.

10. Adrian C. North et al., “The effect of musical style on restaurant consumers’ spending,” Environment and Behavior 35 (2003), pp. 712–718.

11. Jesus Tanguma et al., “Shopping and bargaining in Mexico: The role of women,” The Journal of Applied Business and Economics 9 (2009), pp. 34–40.

12. Katariina Mäenpää et al., “Consumer perceptions of Internet banking in Finland: The moderating role of familiarity,” Journal of Retailing and Consumer Services 15 (2008), pp. 266–276.

13. Sangwon Lee and Seonmi Lee, “Multiple play strategy in global telecommunication markets: An empirical analysis,” International Journal of Mobile Marketing 3 (2008), pp. 44–53.

14. Jeffrey T. Kullgren et al., “Individual- versus group-based financial incentives for weight loss,” Annals of Internal Medicine 158, no. 7 (2013), pp. 505–514.

15. P. Bartel et al., “Attention and working memory in resident anaesthetists after night duty: Group and individual effects,” Occupational and Environmental Medicine 61 (2004), pp. 167–170.

16. Based on M. U. Kalwani and C. K. Yim, “Consumer price and promotion expectations: An experimental study,” Journal of Marketing Research 29 (1992), pp. 90–100.

17. R. Hamilton et al., “We’ll be honest, this won’t be the best article you’ve ever read: The use of dispreferred markers in word-of-mouth communication,” Journal of Consumer Research 41 (2014), pp. 197–212.

1. This example is based on Laura Herrewijn and Karolien Poels, “Recall and recognition of in-game advertising: The role of game control,” Frontiers in Psychology 4 (2014), pp. 1–14.

2. This example is based on Laura Smarandescu and Terence A. Shimp, “Drink Coca-Cola, eat popcorn, and choose Powerade: Testing the limits of subliminal persuasion,” doi:10.1007/s11002-014-9294-1 (2014).

3. This example is based on Shibin Sheng and Yue Pan, “Bundling as a new product introduction strategy: The role of brand image and bundle features,” Journal of Retailing and Consumer Services 16 (2009), pp. 367–376.

4. This example is based on Iana A. Castro et al., “The influence of disorganized shelf displays and limited product quantity on consumer purchase,” Journal of Marketing 77 (2013), pp. 118–133.

5. We present the two-way ANOVA model and analysis for the general case in which the sample sizes may be unequal. If the sample sizes vary a great deal, serious complications can arise. There is no longer a single standard ANOVA analysis. Most computer packages offer several options for the computation of the ANOVA table when group counts are unequal. When the counts are approximately equal, all methods give essentially the same results.

6. U.S. Census Bureau, American Community Survey, 2012 American Community Survey 1-Year Estimates.

7. See Note 3.

8. Example 15.10 is based on a study described in Todd Green and John Peloza, “Finding the right shade of green: The effect of advertising appeal type on environmentally friendly consumption,” Journal of Advertising 43, no. 2 (2014), pp. 128–141.

9. Based on M. U. Kalwani and C. K. Yim, “Consumer price and promotion expectations: An experimental study,” Journal of Marketing Research 29 (1992), pp. 90–100.

10. Jane Kolodinsky et al., “Sex and cultural differences in the acceptance of functional foods: A comparison of American, Canadian, and French college students,” Journal of American College Health 57 (2008), pp. 143–149.

11. Tomas Brodin et al., “Dilute concentrations of a psychiatric drug alter behavior of fish from natural populations,” Science 339 (2013), pp. 814–815.

12. Vincent P. Magnini and Kiran Karande, “The influences of transaction history and thank you statements in service recovery,” International Journal of Hospitality Management 28 (2009), pp. 540–546.

13. Willemijn M. van Dolen, Ko de Ruyter, and Sandra Streukens. “The effect of humor in electronic service encounters,” Journal of Economic Psychology 29 (2008), pp. 160–179.

14. Tamar Kugler et al., “Trust between individuals and groups: Groups are less trusting than individuals but just as trustworthy,” Journal of Economic Psychology 28 (2007), pp. 646–657.

15. S. Leroy, “Why is it so hard to do my work? The challenge of attention residue when switching between work tasks,” Organizational Behavior and Human Decision Processes 109 (2009), pp. 168–181.

16. Margaret C. Campbell and Kevin Lane Keller, “Brand familiarity and advertising repetition effects,” Journal of Consumer Research 30 (2003), pp. 292–304.

17. Based on a problem from Renée A. Jones and Regina P. Becker, Department of Statistics, Purdue University.

18. Debora V. Thompson and Prashant Malaviya, “Consumer-generated ads: Does awareness of advertising co-creation help or hurt persuasion?” Journal of Marketing 77 (2013), pp. 33–17.

19. Lijia Lin et al., “Animated agents and learning: Does the type of verbal feedback they provide matter?” Computers and Education, 2013, doi: 10.1016/j.compedu.2013.04.017.

1. Condé Nast Traveler readers poll data for 2013, from cntraveler.com.

2. This test was invented by Frank Wilcoxon (1892-1965) in 1945. Wilcoxon was a chemist who met statistical problems in his work at the research laboratories of American Cyanimid Company.

3. For purists, here is the precise definition: is stochastically larger than if

>for all , with strict inequality for at least one . The Wilcoxon rank sum test is effective against this alternative in the sense that the power of the test approaches 1 (that is, the test becomes more certain to reject the null hypothesis) as the number of observations increases.

4. Data from Huey Chern Boo, “Consumers’ perceptions and concerns about safety and healthfulness of food served at fairs and festivals,” M.S. thesis, Purdue University, 1997.

5. Discussion forum count taken from University of Wisconsin-Milwaukee MBA course titled “Business Analytics for Managers.”

6. From Sapna Aneja, “Biodeterioration of textile fibers in soil,” M.S. thesis, Purdue University, 1994.

7. Data obtained from data.worldbank.org /indicator.

8. Data loosely based on Alexander Redlein and Michael Zobl, “ERP systems within facility management,” Advanced Research in Scientific Areas Proceedings, December 2013, pp. 153-155.

9. Data provided by Warren Page, New York City Technical College, from a study done by John Hudesman.

10. Data from “Results report on the vitamin C pilot program,” prepared by SUSTAIN (Sharing United States Technology to Aid in the Improvement of Nutrition) for the U.S. Agency for International Development.

11. Data from www.nytimes.com/best-sellers-books.

12. Simplified from the EESEE story “Stepping Up Your Heart Rate.”

13. Data provided by Diana Schellenberg, Purdue University School of Health Sciences.

14. Data provided by Sam Phillips, Purdue University.

15. Data from Olga Goncalves, “Efficiency and productivity of French ski resorts,” Tourism Management 36 (2013), pp. 650-657.

16. Data provided by Helen Park. See H. Park et al., “Fortifying bread with each of three antioxidants,” Cereal Chemistry 74 (1997), pp. 202-206.

17. Data provided by Jo Welch, Purdue University Department of Foods and Nutrition.

18. See Note 6.

19. The 2013 study can be found at www.qsrmagazine.com/content/drive-thru-performance-study-customer-service.

20. Consumer Reports, June 1986, pp. 366-367.

21. Data from Parviz Asheghian, “The managerial efficiencies of Indian firms as compared to American firms,” International Journal of Economics and Management Sciences 6 (2012), pp. 45-55.

22. Based on A. A. Adish et al., “Effect of consumption of food cooked in iron pots on iron status and growth of young children: A randomised trial,” The Lancet 353 (1999), pp. 712-716.

1. Logistic regression models for the general case where there are more than two possible values for the response variable have been developed. These are considerably more complicated and are beyond the scope of our present study. For more information on logistic regression, see A. Agresti, An Introduction to Categorical Data Analysis, 2nd ed., Wiley, 2007; and D. W. Hosmer and S. Lemeshow, Applied Logistic Regression, 3rd ed., Wiley, 2013.

2. Nicolas Guéguen and Céline Jacob, “Clothing color and tipping: Gentlemen patrons give more tips to waitresses with red clothes,” Journal of Hospitality & Tourism Research 38, no. 2 (2014), pp. 275-280.

3. This example is taken from a classical text written by a contemporary of R. A. Fisher. (Fisher developed many of the fundamental ideas of statistical inference that we use today.) The reference is D. J. Finney, Probit Analysis, Cambridge University Press, 1947. Although not included in the analysis, it is important to note that the experiment included a control group that received no insecticide. No aphids died in this group. Also, although we have chosen to call the response “killed,” in the text, the category is described as “apparently dead, moribund, or so badly affected as to be unable to walk more than a few steps.” This is an early example of the need to make careful judgments when defining variables to be used in a statistical analysis. Nevertheless, an insect that is “unable to walk more than a few steps” is unlikely to eat very much of a chrysanthemum plant!

4. Based on Leigh J. Maynard and Malvern Mupan-dawana, “Tipping behavior in Canadian restaurants,” International Journal of Hospitality Management 28 (2009), pp. 597-603.

5. Tom Reichert, “The prevalence of sexual imagery in ads targeted to young adults,” Journal of Consumer Affairs 37 (2003), pp. 403-412.

6. Results from Rayna Brown and Neal Sarma, “CEO overconfidence, CEO dominance and corporate acquisitions,” Journal of Economics and Business 59 (2007), pp. 358-379.

7. Anthony A. Noce and Larry McKeown, “A new benchmark for Internet use: A logistic modeling of factors influencing Internet use in Canada, 2005,” Government Information Quarterly 25 (2008), pp. 462-476.

8. The press release for this survey can be found at the Best Western website, www.bestwestern.com/about-us/press-media/press-release-details.asp?NewsID=910.

9. Based on Greg Clinch, “Employee compensation and firms' research and development activity,” Journal of Accounting Research 29 (1991), pp. 59-78.

10. Michael Lynn and Shou Wang, “The indirect effects of tipping policies on patronage intentions through perceived expensiveness, fairness, and quality,” Journal of Economic Psychology 39 (2013), pp. 62-71.

11. This result can be found at www.pwc.com/gx/en/retail-consumer/retail-consumer-publications/global-multi-channel-consumer-survey/explore-the-data.jhtml.

12. From Karin Weber and Weley S. Roehl, “Profiling people searching for and purchasing travel products on the World Wide Web,” Journal of Travel Research 37 (1999), pp. 291-298.

13. Based on information in “NCAA 2003 national study of collegiate sports wagering and associated health risks,” which can be found at the NCAA website, www.ncaa.org.