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Unformatted text preview: • Read Chapter 12. • See Blackboard for assignment. Due 25 March . • Quiz 5 is postponed until 23 March (the Wednesday after spring break). Chapter 12: Homework • You should be able to recall: • You should be able to accomplish: – Use Minitab to conduct a multiple linear regression. – Use Minitab to plot residuals. – Build regression models with polynomial terms – Test hypotheses and construct confidence intervals on the regression coefficients – Use the regression model to estimate the mean response and to make predictions – Construct confidence and prediction intervals on mean and predicted response – Use stepwise and other model building techniques to select the appropriate set of variables for a regression model. • You should be able to understand: – How to interpret residual plots to assess regression model accuracy. – How to interpret regression coefficients and pvalues – How to interpret the ANOVA pvalue – How to interpret violations of assumptions Chapter 12: Objectives • The last chapter was about simple linear regression. We had some response (y), and we were using a line to create predictions of y for different values of x. • In this chapter there is more than one x. For two predictors, you can visualize this as a plane, where y is predicted as a value on the plane given any values of x 1 and x 2 . • For more than 2 predictors, you can’t visualize it, but it is not any different – we are predicting y based on n predictors (x n ) • The math becomes more dense in this chapter. It is probably not useful for you to follow the derivations or equations associated with MLR. It is useful for you to review the matrix notation, but not necessary for you to follow the matrix algebra either. • Minitab will do everything you need. It is important that you understand how to do a MLR in Minitab and what the output means. Chapter 12: Overview of multiple linear regression • Let’s say we want to see how well a regression model can predict a person’s starting salary given some information about those people. • We’re also going to check how well a person can do the same thing. For that we need a volunteer to make these judgments … Chapter 12: Example Class exercise – predictions (mean = $55,000) Gender Age G_GPA BusExp Major JobType . Male 25 3.25 1 Nontech Finance Male 27 3.32 3 Nontech Finance Male 22 3.65 Nontech Finance Male 26 3 6 Nontech Consulting Male 26 3.68 2 Nontech Finance Male 31 3 6 Tech Other Female 33 3.63 Nontech Consulting Male 28 3.22 2 Nontech Finance Male 28 3.33 3 Nontech Consulting Male 26 3.39 1 Nontech Finance Male 27 3.78 4 Nontech Other Male 28 2.9 Nontech Other Female 26 3.21 2 Nontech Finance Male 27 3.06 3 Nontech Finance Female 27 2.22 4 Nontech Consulting Male 27 3.11 Nontech Finance Male 27 3.39 2 Nontech Finance Female 26 3.17 1 Nontech Finance Male 26 3.79 1 Tech Consulting Male 25 3.8 2 Nontech Consulting . Guess ....
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 Spring '08
 Finance, Regression Analysis, 15240 Consulting

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