This course introduces an arsenal of regression-type statistical models for analyzing social data, including multiple linear regression (MLR) and various extensions and alternatives. Note that this course focuses on practical aspects of various models, involving very limited mathematic proofs when necessary. Through an anatomy of MLR, the course reviews key components of applied regression analysis in social sciences. Such a review pays the way for introducing immediate extensions (e.g. robust regression) and alternatives (quantile regression) for continuous response variables. The course further covers a wide variety of categorical response variable models collectively known as generalized linear models (GLM). The remaining sessions are devoted to certain advanced topics of key significance, including causal inference, hierarchical data structures, and longitudinal data analysis.