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This is a book about regression models for categorical and count data, as they are used in the social sciences. It continues the previous book in the SAGE Quantitative Research Kit series, Volume 7, which introduced linear regression and the principles of statistical modelling. The book you are reading now shows how these principles can be applied when the outcome is a categorical or count variable. Reading Volume 7 of the Kit would be a good preparation for studying this book, but this book does stand on its own. Readers who are already familiar with linear regression can dive straight in. A brief reminder of linear regression is provided in Chapter 1, alongside an introduction to the mathematical notation used throughout. This book is software-neutral. It can be read and understood without using any statistical software. On the other hand, what you learn here can be applied using any statistical software that can estimate regression models. To carry out the analyses reported in this book, I mainly used the free open-source software R (R Core Team, 2019). On a few occasions, I also made use of the commercial software Stata (StataCorp, 2019). Other statistical packages often used by social scientists to estimate regression models are SPSS and SAS.