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Chapter Seventeen. Chapter 17. Figure 17.1 Relationship to the Previous Chapters & The Marketing Research Process. Figure 17.1 Relationship of Hypothesis Testing Related to Differences to the Previous Chapter and the Marketing Research Process. Focus of This Chapter. Relationship to
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Chapter Seventeen Chapter 17
Figure 17.1 Relationship to the Previous Chapters & The Marketing Research Process Figure 17.1 Relationship of Hypothesis Testing Related to Differences to the Previous Chapter and the Marketing Research Process Focus of This Chapter Relationship to Previous Chapters Relationship to Marketing Research Process • Hypothesis Testing Related to Differences • Means • Proportions • Research Questions and Hypothesis (Chapter 2) • Data Analysis Strategy (Chapter 15) • General Procedure of Hypothesis Testing (Chapter 16) Problem Definition Approach to Problem Research Design Field Work Data Preparation and Analysis Report Preparation and Presentation
Figure 17.2 Hypothesis Testing Related to Differences: An Overview Figure 17.2 Hypothesis Testing Related to Differences: An Overview Opening Vignette Hypothesis Testing Related to Differences Figs 17.3-17.5 t-Distribution Testing Hypothesis Internet Applications Focus on Elrick & Lavidge t-Tests Tables 17.1-17.5 One Sample Two Sample Independent Paired Testing Hypothesis for More Than Two Samples Tables 17.6-17.8 Application to Contemporary Issues TQM International Technology Ethics
Figure 17.3 Hypothesis Tests Related to Differences Figure 17.3 Hypothesis Tests Related to Differences Tests of Differences One Sample Two Independent Samples Paired Samples More Than Two Samples Means Means Means Means Proportions Proportions Proportions Proportions
Figure 17.4 Conducting t-Tests Figure 17.4 Conducting t-Tests Formulate H0 and H1 Select Appropriate t-Test Choose Level of Significance, α Collect Data and Calculate Test Statistic a) Determine Probability Associated with Test Statistic (TSCAL) b) Determine Critical Value of Test Statistic TSCR a) Compare with Level of Significance, α b) Determine if TSCR falls into (Non) Rejection Region Reject or Do Not Reject H0 Draw Marketing Research Conclusion
Figure 17.5 Calculating the Critical Value of the Test Statistic: TSCR for Two-Tailed and One-Tailed Tests Figure 17.5 Calculating the Critical Value of the Test Statistic: TSCR for Two-Tailed and One-Tailed Tests α/2 α/2 α
Figure 17.6 Other Computer Programs for t-tests Figure 17.6 Other Computer Programs for t-tests SAS In SAS, the program TTEST can be used to conduct t-tests on independent as well as paired samples MINITAB Parametric test available in MINITAB in descriptive stat function are z-test mean, t-test of the mean, and two-sample t-test. EXCEL The available parametric tests in EXCEL and other spreadsheets include the t-test; paired sample for means; t-test: two independent samples assuming equal variances; t-test: two independent samples assuming unequal variances, z-test: two samples for means, and F test two samples for variances.
Figure 17.7 Other Computer Programs for ANOVA Figure 17.7 Other Computer Programs for ANOVA SAS The main program for performing analysis of variance is ANOVA. This program can handle data from a wide variety of experimental designs. For more complex designs, the more general GLM procedure can be used. While GLM can also be used for analyzing simple designs, it is not as efficient as ANOVA for such models. MINITAB Analysis of Variance can be assessed from the Stats>ANOVA function. This function performs one way ANOVA and can also handle more complex designs. In order to compute the mean and standard deviation, the cross-tab function must be used. To obtain F and p values, use the balanced ANOVA. EXCEL Both a one-way ANOVA and more complex designs can be analyzed under the Tools>Data Analysis function.
Table 17.1 Preference for Disney Before and After Visiting the Resort
Table 17.4 Comparing the Proportions of Jeans Users for the USA and Hong Kong
