Least squares modelling

Learning outcomes

• Understand the difference between correlation and covariance.
• What the objective function of least squares does
• Understand and use an analysis of variance table
• Calculate and interpret the confidence intervals from a least squares model
• Know about the assumptions required to interpret least squares model coefficients
• Use the prediction error range from the model
• Identify outlier points and classify them
• Use the linear model when there are multiple predictor variables (this is what we are building up towards; we will use this extensively in the next topic)

Extended readings/practice

• Run the code below to see how to build and use a linear model in R, but see step 16 and onwards in the R tutorial as well.
• Try some practice problems.
• Does eating chocolate lead to winning a Nobel prize?