CRIJ/POSC/SOCI/SOCW 3362: Statistics for the Social Sciences

Many textbooks on regression focus on theory and the simplest of examples. Real statistical problems, however, are complex and subtle. This is not a book about the theory of regression. It is a book about how to use regression to solve real problems of comparison, estimation, prediction, and causal inference. It focuses on practical issues such as sample size and missing data and a wide range of goals and techniques. It jumps right in to methods and computer code you can use fresh out of the box.

The PDF is free to download for personal use only. Not for re-distribution, re-sale or use in derivative works.

The Research Methods Knowledge Base is a comprehensive web-based textbook that addresses all of the topics in a typical introductory undergraduate or graduate course in social research methods. It covers the entire research process including: formulating research questions; sampling (probability and nonprobability); measurement (surveys, scaling, qualitative, unobtrusive); research design (experimental and quasi-experimental); data analysis; and, writing the research paper. It also addresses the major theoretical and philosophical underpinnings of research including: the idea of validity in research; reliability of measures; and ethics.

Created by Alboukadel Kassambara, STHDA is a training website on data science. It contains many tutorials on data analysis and visualization using R software and packages.

This book introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression and machine learning and helps you develop skills such as R programming, data wrangling with dplyr, data visualization with ggplot2, file organization with UNIX/Linux shell, version control with GitHub, and reproducible document preparation with R markdown.

This ebook shows specific R tools framed within social science applications, along with programming examples.

A short introduction to R, aimed at new users of R.

This book provides a helpful resource for anyone looking to use R for their research projects, regardless of their level of programming or statistical analysis experience. Each chapter presents essential concepts in data analysis in a concise, thorough, and user-friendly manner. R4NP will guide you through your first steps on a possibly endless journey full of ‘awe and wonder’.

This book is designed to be accessible to beginners while also providing valuable insights for experienced analysts looking to transition to R from other computational software. You don’t need any prior knowledge or programming skills to get started. R4NP provides a comprehensive entry into R programming, regardless of your background.