# 1/26/2022

## Problem Session

- Complete exercises 1.34, 1.36, and 1.39

## Complete Chapter 1 - Simple Linear Regression - See Sec1.4-5.ppt

- Outliers
- Influential points

## Class Activity on Robbery Rates - see robbery.dat, robbery.csv, and robbery.R

- A criminologist studying the relationship between population density and robbery rate in medium-sized U.S. cities collected the data for a random sample of 16 cities. The data for X = population density of the city (number of people per unit area) and Y = the robbery rate last year (number of robberies per 100,000 people) can be found in robbery.dat.
- Obtain the estimated regression line. Plot the estimated regression line and the data. Does the simple linear regression model appear to provide a good fit?
- Obtain point estimates of the following:
- the difference in the mean robbery rate in cities that differ by one unit in population density
- the mean robbery rate last year in cities with population density X = 60
- the random error term for the 10th observation
- the variance of the error terms

## R Lab

- Transformation examples from the PPT slides

## Please read Sections 2.1-2.3 for class on Friday.