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Using R for data analysis in social ...

Li, Quan, (1966-)

Using R for data analysis in social sciences :a research project-oriented approach /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Using R for data analysis in social sciences :Quan Li.
Reminder of title:	a research project-oriented approach /
Author:	Li, Quan,
Description:	xix, 341 pages :illustrations ;24 cm
Subject:	Social sciencesResearch
ISBN:	9780190656225

Using R for data analysis in social sciences :a research project-oriented approach /
Li, Quan,1966-

Using R for data analysis in social sciences :a research project-oriented approach /Quan Li. - xix, 341 pages :illustrations ;24 cm

Includes bibliographical references and index.

List of Figures -- List of Tables -- Learn about R and Write First Toy Programs -- Get Data Ready: Import, Inspect, and Prepare Data -- One-Sample and Difference of Means Tests -- Covariance and Correlation -- Regression Analysis -- Regression Diagnostics and Sensitivity Analysis -- Replicate Findings in Published Analyses -- Appendix: A Brief Introduction to Analyzing Discrete Data.

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.--

ISBN: 9780190656225NT$1115

LCCN: 2017010031

Nat. Bib. No.: GBB8D9970bnb

Nat. Bib. Agency Control No.: 018993818UkSubjects--Topical Terms:

268958
Social sciences
--Research

LC Class. No.: H61.3 / L693 2018

Dewey Class. No.: 330.285/5133

Using R for data analysis in social sciences :a research project-oriented approach /
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