Linear models: Estimation

In this unit, we will focus on estimation of coefficients in the linear regression model (eqs. 1.1 and 1.2). We start by discussing the interpretation of linear models (Chapter 2). Then, we discuss least squares estimates from the algebraic, geometric, and probabilistic perspectives (Chapter 3). We then discuss important properties of least squares estimates, including orthogonality relationships least squares estimation implies (Chapter 4) and the effects of collinearity (Chapter 5). We conclude with an R demo (Chapter 6).