Mar_28 - were collected. a. Determine the regression...

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ECM Tutorials March 28-31, 2011 Review: In this tutorial we will: 1. Run linear regressions in Excel2007 2. Explain regression outputs, including R square, adjusted R square, standard error etc. 3. Hypothesis test and confidence intervals on estimated coefficients 4. Plot regression residuals 5. Check multicollinearity Required Menus/Commands: Data->Data Analysis…->Regression Data->Data Analysis…->Histogram Exercises Ex1: (page 688 #17.2) Pat was registered in a statistics course, which had only 3 weeks to go before the final exam. To determine how much work to do in the remaining 3 weeks, Pat needed to be able to predict the final exam mark on the basis of the assignment mark (worth 20 points) and the midterm mark (worth 30 points). Accordingly, Pat undertook a linear regression analysis. The final exam mark, assignment mark, and midterm test mark for 30 students who took the statistics course last year
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Unformatted text preview: were collected. a. Determine the regression equation. b. What is the standard error of estimate? How to interpret this statistics? c. What are the R square and adjusted R square? What is their difference? d. Test the validity of the model. (That is, all coefficients, except the intercept, are equal to 0.) e. Interpret each coefficient in the regression. f. Can Pat infer that the assignment mark is linearly related to the final grade in this model? g. Can Pat infer that the midterm mark is linearly related to the final grade in this model? h. Determine the residuals and predicted values. i. Does it appear that the normality requirement is violated? Explain. j. Is the variance of the error variable constant? Explain....
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This note was uploaded on 05/17/2011 for the course ECO 220 taught by Professor Tanaka during the Spring '11 term at University of Toronto- Toronto.

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