Multiple Regression using SAS
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. Create a new variable called SAT which equals SATM + SATV and run following two regressions:
i. predict GPA using HSM, HSS, and HSE.
ii. predict GPA using SAT, HSM, HSS, and HSE.
Kindly refer to the attachment for full questions and problems. Thanks!
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This solution is comprised of a detailed explanation of Multiple Regression using the SAS. In this solution, step-by-step explanation of this complicated topic provides students with a clear perspective of Regression on different variables using SAS.
Multiple regression problems using SAS output
I have never used SAS before, but I need to answer some multiple regression problems using SAS output.
Please see the attached files. Please label the variable used in answering the question so I can understand what is done.
For a sample of people, three measurements are taken on each person (skin, thigh, arm) in an attempt to obtain variables useful in predicting their body fat (also measured). Output of SAS regression of fat on skin, thigh, and arm variables and regression of fat on skin are given on the following pages.
1. Given a formula(s) to construct a confidence interval for 0+501+202+303. Make it clear that you could calculate the lower and upper bounds if asked. Include the Student's t value for a 95% confidence level.
2. The regression coefficient associated with skin differs in the full and simple linear regression models. Explain the difference.
3. There are 10 confidence intervals in the middle of page D. What confidence level can be associated with the claim that all 10 are correct inferences?
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