Sample_Exam_1 - Sample Exam 1 Part 1: Multiple Linear...

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Sample Exam 1 Part 1: Multiple Linear Regression: 1. A regression line is fit from a sample of size 30. The least squares line is: 2 1 * 2 . 13 * 7 . 4 2 . 2 ˆ x x y + + = , and the standard errors of b1 and b2 are 3.1 and 2.8, respectively. a) Give a 95% confidence interval for 2 β . b) What is the test statistic for the test H0: 0 1 = vs H: 0 1 ? c) Is X1 a significant linear predictor at the 5% level? Why or why not? Is X2 a significant linear predictor at the 5% level? Why or why not? 2. Find the error in the following two statements: a) R square adjusted is not valid whenever there are categorical predictors in the model. b) In multiple linear regression, the outcome variable Y is assumed to be normally distributed. 3. The following regression model was built to analyze the effect of having a corner lot on the selling price of your home. Saleprice is the dependent variable, and is the actual selling price of the home (in thousands of dollars). Assessed is the
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This note was uploaded on 07/25/2008 for the course STT 422 taught by Professor Porter during the Summer '08 term at Michigan State University.

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Sample_Exam_1 - Sample Exam 1 Part 1: Multiple Linear...

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