1. 264a Marketing Research 1 Linear Statistical Models

2. 264a Marketing Research 2 Answering the questions you have asked. Are these ratings really different? What is the influence of a policy variable (price, advertising, and etc.) on a market outcome (market shares, sales, overall satisfaction)? What is the part worth of a particular feature in a whole bundle that makes a product?

3. 264a Marketing Research 3 Are these ratings really different? Comparing one mean to a null hypothesis –One Sample t-test Comparing two samples means to each other –Two Sample t-test What about comparing six mean ratings –Why not 6*5/2 = 15 paired t-tests?

4. 264a Marketing Research 4 Degrees of freedom We are asking if a series of 6 mean ratings are really all the same (the variations around the mean are just noise). We shouldn’t run 15 paired t-tests with only 5 independent pieces of information. A complex pattern of redundancy will make the results deceptive.

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8. 8 Testing Hypotheses about What Facilities are Most Needed Null hypothesis: –The different facilities are all equally needed Alternative hypothesis: –Some kind are rated as more needed than others Test statistic –F =Variance Between Groups/Variance Within – = Signal / Noise Decision Rule: Set Alpha at.05

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10. 10 Once you have found a significant difference overall Post Hoc Comparisons –You can do as many paired t-tests as you want without worrying about redundancy. –You can use advanced test (Range Tests) to see which ratings stand out.