Engaging and accessible, Reasoning with Data: An Introduction to Traditional and Bayesian Statistics Using R teaches readers how to use inferential statistical thinking to check their assumptions, assess evidence about their beliefs, and avoid overinterpreting results that may look more promising than they really are. It provides step-by-step guidance for using both classical (frequentist) and Bayesian approaches to inference. Statistical techniques covered side by side from both frequentist and Bayesian perspectives include hypothesis testing, replication, analysis of variance, calculation of effect sizes, regression, time series analysis, and more. The book introduces the open-source R programming language and its key packages, providing step-by-step guidance for students who may not have a strong background in mathematics. Each chapter includes end-of-chapter exercises based on real data supplied in the free R package, as well as technical explanations and equation/output boxes to aid understanding. Appendices offer additional support with instructions on how to install R and work with sample datasets.