Linear and generalized linear models have been widely used in agronomic research and many other fields. Regression models, which are a subclass of linear models, are important statistical tools in an agronomist's toolkit. The objective of this course is to introduce fundamental theory and practical techniques of regression analysis. Several important topics, including parameter estimation, hypothesis testing, model selection and diagnostics, will be detailed. In addition, R programs will be provided to implement these analysis procedures. After successfully completing this course, students will be able to address real-world research questions using regression analysis.