section10 - Statistics 104 Spring 2011 Section#10 Topics...

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Statistics 104 – Spring 2011 Section #10 Topics for Section Multiple Regression Practice Problems Our political scientist is not satisfied with her prior results She collected more data, and thinks that the following attributes might better explain how a state voted in the 2008 US presidential election. X 1 = state average IQ, X 2 = state population, X 3 = 8 th grade math score gender difference (M - F), X 4 = % of people who eat 5+ vegetables a day, X 5 = % of non-white residents X 6 = {1 if the state is in the South, 0 otherwise} Again, the investigator first looks at the correlations between all the variables. . corr mccainvote iq population thgrademathscoresgenderdiffmf vegetablesaday nonwhite south (obs=50) | mccain~e iq popula~n thgrad~f vegeta~y nonwhite south -------------+--------------------------------------------------------------- mccainvote | 1.0000 iq | -0.1484 1.0000 population | -0.1873 -0.2107 1.0000 thgrademat~f | -0.0499 0.1710 0.2966 1.0000 vegetables~y | -0.6163 0.3036 0.2490 0.0312 1.0000 nonwhite | -0.2010 -0.7350 0.4492 0.0099 0.0266 1.0000 south | 0.4116 -0.4962 0.1321 -0.2458 -0.3141 0.2643 1.0000 a. Which of the covariates will have the most significant simple linear regression fit with the McCain voting percentage? Should we be concerned about multicollinearity? b. Do you believe that these covariates will yield a better predictive model than those selected previously? Why or why not?
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The investigator thinks that these variables will yield the “best” predictive model. As before, she starts with the full model below. . regress mccainvote iq population thgrademathscoresgenderdiffmf vegetablesaday nonwhite south Source | SS df MS Number of obs = 50 -------------+------------------------------ F( 6, 43) = 7.43 Model | .221240481 6 .036873413 Prob > F = 0.0000 Residual | .213345063 43 .004961513 R-squared = 0.5091 -------------+------------------------------ Adj R-squared = 0.4406 Total | .434585544 49 .008869093 Root MSE
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This note was uploaded on 03/27/2012 for the course STATS 104 taught by Professor Michaelparzen during the Fall '11 term at Harvard.

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section10 - Statistics 104 Spring 2011 Section#10 Topics...

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