Description
Question 8.1
Describe a situation or problem from your job, everyday life, current events, etc., for which a linear
regression model would be appropriate. List some (up to 5) predictors that you might use.
Question 8.2
Using crime data from http://www.statsci.org/data/general/uscrime.txt (description at
http://www.statsci.org/data/general/uscrime.html ), use regression (a useful R function is lm or glm) to
predict the observed crime rate in a city with the following data:
M = 14.0
So = 0
Ed = 10.0
Po1 = 12.0
Po2 = 15.5
LF = 0.640
M.F = 94.0
Pop = 150
NW = 1.1
U1 = 0.120
U2 = 3.6
Wealth = 3200
Ineq = 20.1
Prob = 0.04
Time = 39.0
Show your model (factors used and their coefficients), the software output, and the quality of fit.
Note that because there are only 47 data points and 15 predictors, you’ll probably notice some
overfitting. We’ll see ways of dealing with this sort of problem later in the course.
