Using R for Data Analysis in Social Sciences

Statistical analysis is common in the social sciences and among the more popular programs is R. This book provides a foundation for undergraduate and graduate students in the social sciences on how to use R to manage visualize and analyze data. The focus is on how to address substantive questions with data analysis and replicate published findings.Using R for Data Analysis in Social Sciences adopts a minimalist approach and covers only the most important functions and skills in R to conduct reproducible research. It emphasizes the practical needs of students using R by showing how to import inspect and manage data understand the logic of statistical inference visualize data and findings via histograms boxplots scatterplots and diagnostic plots and analyze data using one-sample t-test difference-of-means test covariance correlation ordinary least squares (OLS) regression and model assumption diagnostics. It also demonstrates how to replicate the findings in published journal articles and diagnose model assumption violations. Because the book integrates R programming the logic and steps of statistical inference and the process of empirical social scientific research in a highly accessible and structured fashion it is appropriate for any introductory course on R data analysis and empirical social-scientific research.