Description
Oxford Using R for Data Analysis in Social Sciences A Research ProjectOriented Approach 2018 Edition by Quan Li
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 theprocess 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. Table of Contents :- List of FiguresList of Tables1. Learn about R and Write First Toy Programs2. Get Data Ready: Import, Inspect, and Prepare Data3. One-Sample and Difference of Means Tests4. Covariance and Correlation5. Regression Analysis 6. Regression Diagnostics and Sensitivity Analysis7. Replicate Findings in Published Analyses 8. Appendix: A Brief Introduction to Analyzing Discrete Data