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Using R for Data Analysis in Social Sciences: A Research Project-Oriented Approach

Using R for Data Analysis in Social Sciences: A Research Project-Oriented Approach

Using R for Data Analysis in Social Sciences: A Research Project-Oriented
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Using R for Data Analysis in Social Sciences: A Research Project-Oriented Approach Paperback - 2018

by Li, Quan

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Oxford University Press, 2018-06-06. paperback. Used: Good. 0.90x9.00x6.10. Buy with confidence. Excellent Customer Service & Return policy.
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  • Title Using R for Data Analysis in Social Sciences: A Research Project-Oriented Approach
  • Author Li, Quan
  • Binding Paperback
  • Condition Used: Good
  • Pages 368
  • Volumes 1
  • Language ENG
  • Publisher Oxford University Press
  • Publication date 2018-06-06
  • Bookseller's Inventory # SONG0190656220
  • ISBN 9780190656225 / 0190656220
  • Weight 1.15 lbs (0.52 kg)
  • Dimensions 9.1 x 6.1 x 0.9 in (23.11 x 15.49 x 2.29 cm)
  • Size 0.90x9.00x6.10
  • Category Business / Economics / Finance
  • Library of Congress subjects Social sciences - Statistical methods, R (Computer program language)
  • Library of Congress Catalogue Number 2017010031
  • Dewey Decimal Code 330.285
  • Quantity available 1

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Reader reviews for Using R for Data Analysis in Social Sciences: A Research Project-Oriented Approach

From the publisher

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.

About the author

Dr. Quan Li is Professor of Political Science at Texas A&M University. His research has appeared in over thirty articles in numerous journals and two coauthored books, Democracy and Economic Openness in an Interconnected System: Complex Transformations and Politics and Foreign Direct Investment. He has served on the editorial boards of American Journal of Political Science, Journal of Politics, International Studies Quarterly, and International Interactions.
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