Linear and generalized linear models are useful tools for agronomic research, which have been widely used in the analysis of field trails and breeding studies. The aim of this course is to introduce linear regression model and its applications. The contents of this course cover two parts: matrix algebra and regression analysis. Matrix algebra is a necessary basis for studying linear and other more complicated models. Based on matrix algebra, several important topics in regression analysis, including parameter estimation, hypothesis testing, model selection and diagnostics, will then be introduced. Students will also learn how to use R to analyze real-life data.