Q.Load the Boston housing data (Boston) from the package MASS. This data contain housing values and hedonic characteristics for 506 areas in the Boston suburbs. Were going to try to predict median value of homes (medv) as a function of neighborhood characteristics. First, summarize the dataset, and use ggpairs or other visualization tools to familiarize yourself with the data. Next regress median housing values against crime rate, average number of rooms per dwelling, age, distance to downtown, and pupil-teacher ratio. Interpret each coefficient in your own words.

Q.Use the orings data set from the package DAAG to estimate a Poisson model of the number of total o-ring incidents (either blow-by or erosion) as a function of temperature. Plot a histogram of the total number of incidents. Does this look Poisson distributed? Test for over-dispersion and if it fails estimate a model that is robust to Poisson over-dispersion.