[19] In the following regression, which are the three best predictors? [1.5 point]
Variables Coefficients Std. Error t (df = 81) p-value
Intercept 9.8080 16.9900 0.577 .5654
NumCyl − 1.6804 0.5757 − 2.919 .0045
HPMax − 0.0369 0.0140 − 2.630 .0102
ManTran 0.2868 1.2802 0.224 .8233
Length 0.1109 0.0601 1.845 .0686
Wheelbase − 0.0701 0.1714 − 0.409 .6836
Width 0.4079 0.2922 1.396 .1665
RearStRm − 0.0085 0.2018 − 0.042 .9666
Weight − 0.0025 0.0020 − 1.266 .2090
Domestic − 1.2291 1.1391 − 1.079 .2838
A) ManTran, Wheelbase, RearStRm
B) ManTran, Length, Width
C) NumCyl, HPMax, Length
D) Cannot be ascertained from the given information
[20] Which of the following would be most useful in checking the normality assumption of the
errors in a regression model? [1.5 point]
A) The t statistics for the coefficients.
B) The F-statistic from the ANOVA table.
C) The histogram of residuals.
D) The VIF statistics for the predictors.
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[21] To find which predictors are most helpful in increasing R2, we might consider
[1.5 point]
A) Log transformations.
B) Stepwise regression.
C) Logistic regression.
D) Nonlinear regression.