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This problem is to be solved using Minitab. Below are the results of an annual survey conducted by Video Board Tests, Inc., a New York ad-testing company, based on interviews with adults who were asked to name the most outstanding TV commercial they had seen, noticed, and liked. These retained impressions are listed along with company name and TV ad expenditures. We would be interested in determining if the number of retained impressions is linearly related to the advertising expenditures (i.e. the more spent on advertising, the higher the number of retained impressions)Variables:
FIRM: Firm nameSPEND: TV advertising budget, 1983 ($ millions)MILIMP: Millions of retained impressions per week
FIRM SPEND MILIMP
MILLER LITE 50.1 32.1PEPSI 74.1 99.6STROH'S 19.3 11.7FED'L EXPRESS 22.9 21.9BURGER KING 82.4 60.8COCO-COLA 40.1 78.6MC DONALD'S 185.9 92.4MCI 26.9 50.7DIET COLA 20.4 21.4FORD 166.2 40.1LEVI'S 27.0 40.8BUD LITE 45.6 10.4ATT/BELL 154.9 88.9CALVIN KLEIN 5.0 12.0WENDY'S 50.1 29.2POLAROID 26.9 38.0SHASTA 5.0 10.0MEOW MIX 7.6 12.3OSCAR MEYER 9.2 23.4CREST 32.4 71.1KIBBLES 'N BITS 6.1 4.4
Perform a complete regression analysis using Minitab to determine whether or not the simple linear regression model is appropriate for this data. Your analysis must include a written analysis (i.e. interpretation of the output) in addition to the Minitab output (this does not mean simply writing notes on the output). For any tests, use α = 0.05. Attach your Minitab output when handing in your assignment.
Do a complete regression analysis by performing the steps below. Note: No regression should be done when r is not significant. Draw a scatter plot. Compute the correlation coefficient.
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