# Multiple linear Regression

Homework 5 ---------- Do the following problems from the textbook (see notes below!):

6.2, 6.5(a,b,d), 6.6(a,b), 6.7(a), 6.8, 6.18(c,e), 6.19(a,c), 6.22(a, c), 6.23(a), 3.3(c,d), 3.6(b,c), 3.16(a, c, d, e, f).

NOTE: Problems 6.5, 6.6, 6.7, 6.8, 6.18, 6.19, 3.3, 3.3, and 3.16 require analysis using a computer package such as SAS or R.

NOTE: For 6.5(a) use pairs(brand) and cor(brand) in R NOTE: For 6.5(d) and 6.18(e), you only need to do the residual plot of the residuals against the predicted values, Y-hat (i.e., the type of plot we did an example of in class). You may optionally do the plots of the residuals against the other terms the book mentions.

NOTE: For 6.8, interpret both the confidence interval and the prediction interval.

NOTE: For 6.23(a), will be counted as a 5 point bonus added to Exam 1. Do NOT use any resources but your notes and the textbook.

NOTE: For 3.16(c), note that the function for base-10 logarithms is log10( ), both in SAS and in R.

The "Brand Preference", "Commercial Properties", and "Solution Concentration" data sets are given on D2L.

Please write your answers neatly and clearly!