1. Chapter XV Frequency Distribution, Cross-Tabulation, and Hypothesis Testing Chapter XV

2. Chapter Outline Chapter Outline 1) Overview 2) Frequency Distribution 3) Statistics Associated with Frequency Distribution i. Measures of Location i. Measures of Location ii. Measures of Variability ii. Measures of Variability iii. Measures of Shape iii. Measures of Shape 4) Introduction to Hypothesis Testing 5) A General Procedure for Hypothesis Testing

3. 6) Cross-Tabulations i. Two Variable Case i. Two Variable Case ii. Three Variable Case ii. Three Variable Case iii. General Comments on Cross-Tabulations iii. General Comments on Cross-Tabulations 7) Statistics Associated with Cross-Tabulation i. Chi-Square i. Chi-Square ii. Phi Correlation Coefficient ii. Phi Correlation Coefficient iii. Contingency Coefficient iii. Contingency Coefficient iv. Cramer’s V iv. Cramer’s V v. Lambda Coefficient v. Lambda Coefficient vi. Other Statistics vi. Other Statistics

4. 8) Cross-Tabulation in Practice 8) Cross-Tabulation in Practice 9) Hypothesis Testing Related to Differences 9) Hypothesis Testing Related to Differences 10) Parametric Tests i. One Sample i. One Sample ii. Two Independent Samples ii. Two Independent Samples iii. Paired Samples iii. Paired Samples 11) Non-parametric Tests i. One Sample i. One Sample ii. Two Independent Samples ii. Two Independent Samples iii. Paired Samples iii. Paired Samples

5. 12) Internet and Computer Applications 13) Focus on Burke 14) Summary 15) Key Terms and Concepts 16) Acronyms

6. RESPONDENT SEX FAMILIARITY INTERNETATTITUDE TOWARD USAGE OF INTERNET NUMBER USAGEInternetTechnology Shopping Banking 1 1.00 7.00 14.007.006.00 1.001.00 2 2.00 2.00 2.003.003.00 2.002.00 3 2.00 3.00 3.004.003.00 1.002.00 4 2.00 3.00 3.007.005.00 1.002.00 5 1.00 7.00 13.007.007.00 1.001.00 6 2.00 4.00 6.005.004.00 1.002.00 7 2.00 2.00 2.004.005.00 2.002.00 8 2.00 3.00 6.005.004.00 2.002.00 9 2.00 3.00 6.006.004.00 1.002.00 10 1.00 9.00 15.007.006.00 1.002.00 11 2.00 4.00 3.004.003.00 2.002.00 12 2.00 5.00 4.006.004.00 2.002.00 13 1.00 6.00 9.006.005.00 2.001.00 14 1.00 6.00 8.003.002.00 2.002.00 15 1.00 6.00 5.005.004.00 1.002.00 16 2.00 4.00 3.004.003.00 2.002.00 17 1.00 6.00 9.005.003.00 1.001.00 18 1.00 4.00 4.005.004.00 1.002.00 19 1.00 7.00 14.006.006.00 1.001.00 20 2.00 6.00 6.006.004.00 2.002.00 21 1.00 6.00 9.004.002.00 2.002.00 22 1.00 5.00 5.005.004.00 2.001.00 23 2.00 3.00 2.004.002.00 2.002.00 24 1.00 7.00 15.006.006.00 1.001.00 25 2.00 6.00 6.005.003.00 1.002.00 26 1.00 6.00 13.006.006.00 1.001.00 27 2.00 5.00 4.005.005.00 1.001.00 28 2.00 4.00 2.003.002.00 2.002.00 29 1.00 4.00 4.005.003.00 1.002.00 30 1.00 3.00 3.007.005.00 1.002.00 Internet Usage Data Table 15.1

7. Frequency Histogram Figure 15.1 2 3 4 5 6 7 0 7 4 3 2 1 6 5 Frequency Familiarity 8

8. Skewness of a Distribution Figure 15.2 Skewed Distribution Symmetric Distribution Mean Median Mode (a) Mean Median Mode (b)

9. Formulate H 0 and H 1 Steps Involved in Hypothesis Testing Fig. 15.3 Select Appropriate Test Collect Data and Calculate Test Statistic Determine Probability Associated with Test Statistic Choose Level of Significance,  Draw Marketing Research Conclusion Reject or Do not Reject H 0 Determine Critical Value of Test Statistic TSCR Determine if TSCR falls into (Non) Rejection Region Compare with Level of Significance, 

10. Probabilities of Type I & Type II Error Figure 15.4 99% of Total Area Critical Value of Z   = 15   = 17  = 0.01 = 1.645 Z  = -2.33 Z  Z Z 95% of Total Area  = 0.05

11. Unshaped Area = 0.0336 Probability of z with a One-Tailed Test Fig. 15.5 Shaded Area = 0.9664 z = 1.83 0

12. Hypothesis Tests Distributions A Broad Classification of Hypothesis Tests Tests of Association Tests of Differences Median/ Rankings Means Proportions Figure 15.6

13. Frequency Distribution of Familiarity with the Internet Table 15.2

14. Gender and Internet Usage Table 15.3

15. Internet Usage by Sex Internet Usage by Sex Table 15.4

16. Original Two Variables Introduce a Third Variable Some Association between the Two Variables Introduction of a Third Variable in Cross-Tabulation Fig. 15.7 Introduce a Third Variable No Association between the Two Variables Some Association between the Two Variables Refined Association between the Two Variables No Change in the Initial Pattern

17. Sex by Internet Usage Table 15.5

18. Purchase of Fashion Clothing by Marital Status Table 15.6

19. Purchase of Fashion Clothing by Marital Status Table 15.7 Unmarried

20. Ownership of Expensive Automobiles by Education Level Table 15.8

21. Ownership of Expensive Automobiles by Education Level and Income Levels Table 15.9

22. Desire to Travel Abroad by Age Table 15.10

23. Desire to Travel Abroad by Age and Sex Table 15.11

24. Eating Frequently in Fast Food Restaurants by Family Size Table 15.12

25. Chi-Square Distribution Figure 15.8 Reject H 0 Do Not Reject H 0 Critical Value 22

26. Independent Samples One Sample Two or More Samples One Sample Two or More Samples Paired Samples Independent Samples Paired Samples * t test * Z test * Chi-Square * K-S * Runs * Binomial * Two-Group t test * Z test * Paired t test * Chi-Square * Mann-Whitney * Median * K-S * Sign * Wilcoxon * McNemar * Chi-Square Hypothesis Tests Parametric Tests (Metric Tests) Non-parametric Tests (Nonmetric Tests) A Classification of Hypothesis Testing Procedures for Examining Differences Fig. 15.9

27. Eating Frequently in Fast Food Restaurants by Family Size & Income Table 15.13

28. Two Independent-Samples t Tests Table 15.14 -

29. Paired-Samples t Test Table 15.15

30. K-S One-Sample Test for Normality For Internet Usage Table 15.16

31. Mann-Whitney U - Wilcoxon Rank Sum W Test Internet Usage by Sex Table 15.17

32. Wilcoxon Matched-Pairs Signed-Rank Test Internet With Technology Table 15.18

33. A Summary of Hypothesis Tests Related to Differences Table 15.19 Contd.

34. Table 15.19 Contd.

35. RIP15.1 In the 90s, the trend is toward global marketing. How can marketers market a brand abroad where there exists diverse historical and cultural differences. According to Bob Kroll, the former president of Del Monte International, uniform packaging may be an asset, yet, catering to individual countries' culinary taste preferences is more important. One recent survey on international product marketing makes this clear. Marketing executives now believe it's best to think globally but act locally. Respondents included 100 brand and product managers and marketing people from some of the nation's largest food, pharmaceutical, and personal product companies. 39% said that it would not be a good idea to use uniform packaging in foreign markets while 38% were in favor of it. Those in favor of regionally targeted packaging, however, mentioned the desirability of maintaining as much brand equity and package consistency as possible from market to market. International Brand Equity - The Name Of The Game

36. RIP15.1 Contd. But they also believed it was necessary to tailor the package to fit the linguistic and regulatory needs of different markets. Based on this finding, a suitable research question can be: Do consumers in different countries prefer to buy global name brands with different packaging customized to suit their local needs? Based on this research question, one can frame a hypothesis that other things being constant, standardized branding with customized packaging for a well established name brand will result in greater market share. The hypotheses may be formulated as follows: H0: Standardized branding with customized packaging for a well established name brand will not lead to greater market share in the international market. H1: Other factors remaining equal, standardized branding with customized packaging for a well established name brand will lead to greater market share in the international market.

37. RIP15.1 Contd. To test the null hypothesis, a well established brand like Colgate toothpaste which has followed a mixed strategy can be selected. The market share in countries with standardized branding and standardized packaging can be compared with market share in countries with standardized branding and customized packaging, after controlling for the effect of other factors. A two independent samples t test can be used.

38. RIP15.2 Descriptive statistics indicate that the public perception of ethics in business, and thus ethics in marketing, are poor. In a poll conducted by Business Week, 46% of those surveyed said that the ethical standards of business executives are only fair. A Time magazine survey revealed that 76% of Americans felt that business managers (and thus researchers) lacked ethics and this lack contributes to the decline of moral standards in the U.S. However, the general public is not alone in its disparagement of business ethics. In a Touche Ross survey of businesspersons, results showed that the general feeling was that ethics were a serious concern and media portrayal of the lack of ethics in business has not been exaggerated. Statistics Describe Distrust