Chapter 13 Linear Regression

Learning Objectives

  1. Explain what is meant by response and explanatory variables.
  2. State the simple regression model (with a single explanatory variable).
  3. Derive the least squares estimates of the slope and intercept parameters in a simple linear regression model.
  4. Use R to fit a simple linear regression model to a data set and interpret the output.
  • Perform statistical inference on the slope parameter.
  • Describe the use of measures of goodness of fit of a linear regression model.
  • Use a fitted linear relationship to predict a mean response or an individual response with confidence limits.
  • Use residuals to check the suitability and validity of a linear regression model.
  1. State the multiple linear regression model (with several explanatory variables).
  2. Use R to fit a multiple linear regression model to a data set and interpret the output.
  3. Use measures of model fit to select an appropriate set of explanatory variables.

Theory

R Practice