14 - Simple and multiple linear regression (Dec. 7-13)
Simple and Multiple Linear Regression Means
Learning Objectives
Regression analysis describes and assesses the significance of relationships between variables.
Provide a description for each of the main goals of regression analysis:
Estimate the regression line based on some data.
Measure the strength of the linear relationship with correlation.
Use the estimated equation for predictions.
Assess if the linear relationship is statistically significant.
Provide interval estimates (confidence intervals) for our predictions.
Understand and check the assumptions of our model.
Be able to describe a linear relationship with a regression line and understand the goal of finding the “best fitting” line.
Define key notation such as predicted y, estimated y, and the slope.
Be able to estimate regression parameters using the method of least squares.
Be able to calculate residuals by subtracting the predicted from the observed response.
Identify the predicted means and predicted outcome values.
Name the regression diagnostics used to confirm the goodness of fit of the model.
Be able to apply the same concepts of simple linear regression to multiple linear regression, where the response variable depends on more than one explanatory variable.