Applied statistics using R : a guide for the social sciences / created by Mehmet Mehmetoglu and Matthias Mittner.

Includes bibliographical references and index.

Chapter 1: Introduction to RChapter 2: Importing and working with data in RChapter 3: How does R work?Chapter 4: Data managementChapter 5: Data visualisation with ggplot2Chapter 6: Descriptive statisticsChapter 7: Simple (bivariate) regressionChapter 8: Multiple linear regressionChapter 9: Dummy-variable regressionChapter 10: Moderation/interaction analysis using regressionChapter 11: Logistic regressionChapter 12: Multilevel and longitudinal analysisChapter 13: Factor analysisChapter 14: Structural equation modellingChapter 15: Bayesian statistics

If you want to learn to use R for data analysis but aren't sure how to get started, this practical book will help you find the right path through your data. Drawing on real-world data to show you how to use different techniques in practice, it helps you progress your programming and statistics knowledge so you can apply the most appropriate tools in your research. It starts with descriptive statistics and moves through regression to advanced techniques such as structural equation modelling and Bayesian statistics, all with digestible mathematical detail for beginner researchers. The book: Shows you how to use R packages and apply functions, adjusting them to suit different datasets. Gives you the tools to try new statistical techniques and empowers you to become confident using them. Encourages you to learn by doing when running and adapting the authors' own code. Equips you with solutions to overcome the potential challenges of working with real data that may be messy or imperfect. Accompanied by online resources including screencast tutorials of R that give you step by step guidance and R scripts and datasets for you to practice with, this book is a perfect companion for any student of applied statistics or quantitative research methods courses