This preview shows pages 1–2. Sign up to view the full content.
This preview has intentionally blurred sections. Sign up to view the full version.View Full Document
Unformatted text preview: Statistics 512: Final Project Due Friday, December 10, 2010 Use the computer science data csdata.dat that we have been discussing in class. The variables are: id , a numerical identifier for each student; GPA , the grade point average after three semesters; HSM ; HSS ; HSE ; SATM ; SATV , which were all explained in class; and GENDER , coded as 1 for men and 2 for women. 1. In this exercise you will illustrate some of the ideas described in Chapter 7 of the text related to the extra sums of squares. (a) Create a new variable called SAT which equals SATM + SATV and run the following two regressions: i. predict GPA using HSM , HSS , and HSE ; ii. predict GPA using SAT , HSM , HSS , and HSE . Calculate the extra sum of squares for the comparison of these two analyses. Use it to construct the F-statistic in other words, the general linear test statistic for testing the null hypothesis that the coefficient of the SAT variable is zero in the model with all four predictors. What are the degrees of freedom for this test statistic?...
View Full Document
This note was uploaded on 04/23/2011 for the course STAT 512 taught by Professor Staff during the Spring '08 term at Purdue University-West Lafayette.
- Spring '08