Hypothesis Testing with R: A Practical Guide for Students

Synopsis

This book provides a comprehensive guide to hypothesis testing using R, designed specifically for university and graduate students. It covers fundamental concepts, various statistical tests, and practical applications, all implemented using the R programming language. Each chapter includes clear explanations, step-by-step examples, and exercises to reinforce learning. The book begins with an introduction to the principles of hypothesis testing, covering topics such as null and alternative hypotheses, p-values, and significance levels. It then delves into specific tests, including t-tests, ANOVA, chi-squared tests, and non-parametric tests, demonstrating how to perform these tests in R. Real-world datasets and case studies are used throughout the book to illustrate the practical relevance of hypothesis testing in various fields. By the end of this book, readers will have a solid understanding of hypothesis testing and the ability to apply these techniques to their own research projects using R.