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Quantitative Analysis for Management Chapter 4

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C H A P T E R

Regression Models

4
15 9 40 20 25 25 15 35 6 4 16 6 13 9 10 16

TEACHING SUGGESTIONS
Teaching Suggestion 4.1: Which Is the Independent Variable? We find that students are often confused about which variable is independent and which is dependent in a regression model. For example, in Triple A’s problem, clarify which variable is X and which is Y. Emphasize that the dependent variable (Y ) is what we are trying to predict based on the value of the independent (X) variable. Use examples such as the time required to drive to a store and the distance traveled, the totals number of units sold and the selling price of a product, and the cost of a computer and the processor speed. Teaching Suggestion 4.2: Statistical Correlation Does Not Always Mean Causality. Students should understand that a high R2 doesn’t always mean one variable will be a good predictor of the other. Explain that skirt lengths and stock market prices may be correlated, but raising one doesn’t necessarily mean the other will go up or down. An interesting study indicated that, over a 10-year period, the salaries of college professors were highly correlated to the dollar sales volume of alcoholic beverages (both were actually correlated with inflation). Teaching Suggestion 4.3: Give students a set of data and have them plot the data and manually draw a line through the data. A discussion of which line is “best” can help them appreciate the least squares criterion. Teaching Suggestion 4.4: Select some randomly generated values for X and Y (you can use random numbers from the random number table in Chapter 15 or use the RAND function in Excel). Develop a regression line using Excel and discuss the coefficient of determination and the F-test. Students will see that a regression line can always be developed, but it may not

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