A Student’s Guide to Statistics Using R

Statistics doesn’t have to feel confusing or intimidating. Written by authors who genuinely love statistics, A Student’s Guide to Statistics Using R introduces core methods through a clear model-building approach—helping students understand how statistics works, why it matters, and how to use R with confidence.

Statistics doesn’t have to feel confusing or intimidating.

Written by authors who genuinely love statistics, A Student’s Guide to Statistics Using R offers a clear, confidence-building introduction to quantitative analysis for the social sciences. It introduces core statistical methods through a coherent model-building approach, helping students understand how statistics works, why it matters for social research, and how different techniques fit together.

Covering all the key methods students encounter in social science degrees—including t-tests, regression, ANOVA, confidence intervals, hypothesis testing, and Bayesian approaches—the book shows how statistical models make sense of messy, real-world data. R is introduced step by step, with clear explanations of code and output so students understand the analysis and can work with confidence, not guesswork.

By focusing on underlying principles rather than rules, this book builds lasting understanding and prepares students for more advanced statistical challenges.

For undergraduate and postgraduate social science students learning statistics and data analysis using R.