Filling a key need, this book provides a gateway to modern data analytics written expressly for social researchers and students. Rex B. Kline builds on readers’ statistical strengths and fills in the gaps from their traditional training. Chapters on programming, data visualization, big data, and supervised and unsupervised machine learning emphasize concepts over equations and feature rich graphics, including 11 color plates. Throughout, worked-through examples with real and simulated data, along with detailed interpretation of the R code and output, prepare readers to apply the techniques. Kline also provides pointers on the pitfalls and advantages of different statistical and data science techniques and explores incorrect interpretations. The companion website supplies R-generated syntax, output, and graphics files for the book's examples; complete data sets; chapter appendices with explanations of the syntax files; and primers on bivariate and multiple regression fundamentals, standard errors and classical significance tests, and data screening and preparation.

Pedagogical Features

• Chapter-opening objectives and key concepts.
• End-of-chapter summaries.
• Exercises with end-of-book answers.
• Annotated suggested readings. Key terms for review.