This chapter introduces regression analysis, focusing on three commonly used types: bivariate, multiple, and logistic regression. Bivariate regression examines the relationship between two scale variables, multiple regression explores how two or more independent variables predict a scale dependent variable, and logistic regression assesses how one or more independent variables predict a binary outcome. Key concepts, including correlation coefficients, regression equations, effect sizes, and statistical assumptions, are explained with practical examples and R code demonstrations. While the chapter covers foundational models, more advanced regression techniques, such as ordinal logistic regression, are addressed in later chapters and subsequent books in the series.