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Assignment # 4 Chapter 3, sections 3.1 and 3.2
Useful videos for using R:
Intro to Multiple Regression R commands: lm(), aov(), summary(aov()), pairs(), cor(). Also
discussed is removing variables for which the is not statistically
significant, and confidence intervals for the ′ .
Residuals and predictions
R commands resid() and predict(). You knew you had to check
conditions for the residuals, right?
1. Do and write-up responses for Problem 3.17.
One does not need any R calculations for this, though you do need the critical t-value for
a confidence interval. In this problem the degrees of freedom is n-k-1 = 232 – 4. The R
command qt(c(0.95,0.975,0.995),232-4) will give you the t-critical values for a 90%,
95% and 99% confidence interval: 1.651564, 1.970423, 2.597564.
Changes: parts a and b ask only about β2, the coefficient for the variable Wgt. Please also
do each part for both β1 and β3, also. If you wish, use a 95% or 99% confidence interval
instead of 90%.
2.
Do and write-up responses for Problem 3.18.
The data file required is posted on D2L, RailsTrails.csv. There is a lot of data, and a
desktop version of R is really needed.
3.
Do and write-up responses for Problem 3.19.
The data file required is posted on D2L, RacialAnimus.csv. There is a lot of data, and a
desktop version of R is really needed.
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