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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.
This book investigates how students in the social sciences can effectively utilize the R programming language to manage, visualize, and analyze empirical data. Author Quan Li provides a structured, minimalist framework designed for undergraduate and graduate students who need to bridge the gap between statistical theory and practical research application. By focusing on essential functions and the replication of published findings, the text serves as a bridge for those conducting reproducible social scientific research.
What You Will Find
Scope Limits
Instructors and students frequently highlight the book's accessibility and its focus on practical, reproducible research workflows. It is widely regarded as a functional introductory text for those seeking to apply R to specific social science research questions.
Page Count:
224
Publication Date:
2018-01-01
Publisher:
Oxford University Press
ISBN-10:
0190656239
ISBN-13:
9780190656232
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