Chapter 16 - Statistical testing of differences and relationships. This chapter addresses statistical techniques that can be used to determine whether observed differences are likely to be real differences or whether they are likely attributable to sampling error. | Chapter Sixteen 16-1 Evaluating Differences and Changes The issue of whether certain measurements are different from one another is central to many questions of critical interest to marketing managers. See the text for some specific examples of managers’ questions relating to evaluating these differences and changes. 16-2 Key Terms & Definitions Bringing some specific examples out in class might help in explaining these concepts. Mathematical Differences: By definition, if numbers are not exactly the same, they are different. This does not, however, mean that the difference is either important or statistically significant. Statistical Significance: A difference that is large enough that it is not likely to have occurred because of chance or sampling error. Statistical Significance 16-3 Key Terms & Definitions Important Differences for Managers: One must be able to distinguish between mathematical differences and statistically significant differences in using the data analysis in . | Chapter Sixteen 16-1 Evaluating Differences and Changes The issue of whether certain measurements are different from one another is central to many questions of critical interest to marketing managers. See the text for some specific examples of managers’ questions relating to evaluating these differences and changes. 16-2 Key Terms & Definitions Bringing some specific examples out in class might help in explaining these concepts. Mathematical Differences: By definition, if numbers are not exactly the same, they are different. This does not, however, mean that the difference is either important or statistically significant. Statistical Significance: A difference that is large enough that it is not likely to have occurred because of chance or sampling error. Statistical Significance 16-3 Key Terms & Definitions Important Differences for Managers: One must be able to distinguish between mathematical differences and statistically significant differences in using the data analysis in managerial decision making. Hypothesis: Assumption or theory that a researcher or manager makes about some characteristic of the population under study. Statistical Significance 16-4 Key Terms & Definitions Examples might help here. You might want to stress that a hypothesis is not always mathematically quoted, and many times it is just a hunch or an educated guess based on secondary information. Step One: Stating the hypothesis “Null Hypothesis” – The hypothesis of status quo, no difference, no effect. “Alternative Hypothesis” - another alternative is proven to be true. Step Two: Choosing the appropriate test statistic Test of means, test of proportions, ANOVA, etc. Step Three: Developing a decision rule Determine the significance level. Needed to determine whether to reject or fail to reject the null hypothesis. The Key Steps: Hypothesis Testing 16-5 Key Terms & Definitions Step Four: Calculating the value of the test statistic Use the appropriate formula to calculate the value of .
