An R Companion to Political Analysis

Nonfiction, Social & Cultural Studies, Political Science, Politics, History & Theory
Cover of the book An R Companion to Political Analysis by Philip H. Pollock, Professor Barry C. Edwards, SAGE Publications
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Author: Philip H. Pollock, Professor Barry C. Edwards ISBN: 9781506368832
Publisher: SAGE Publications Publication: March 31, 2017
Imprint: CQ Press Language: English
Author: Philip H. Pollock, Professor Barry C. Edwards
ISBN: 9781506368832
Publisher: SAGE Publications
Publication: March 31, 2017
Imprint: CQ Press
Language: English

Teach your students to conduct political research using R, the open source programming language and software environment for statistical computing and graphics. An R Companion to Political Analysis by Philip H. Pollock III and Barry C. Edwards offers the same easy-to-use and effective style as the best-selling SPSS and Stata Companions. The all-new Second Edition includes new and revised exercises and datasets showing students how to analyze research-quality data to learn descriptive statistics, data transformations, bivariate analysis (cross-tabulations and mean comparisons), controlled comparisons, statistical inference, linear correlation and regression, dummy variables and interaction effects, and logistic regression. The clear explanation and instruction is accompanied by annotated and labeled screen shots and end-of-chapter exercises to help students apply what they have learned.

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Teach your students to conduct political research using R, the open source programming language and software environment for statistical computing and graphics. An R Companion to Political Analysis by Philip H. Pollock III and Barry C. Edwards offers the same easy-to-use and effective style as the best-selling SPSS and Stata Companions. The all-new Second Edition includes new and revised exercises and datasets showing students how to analyze research-quality data to learn descriptive statistics, data transformations, bivariate analysis (cross-tabulations and mean comparisons), controlled comparisons, statistical inference, linear correlation and regression, dummy variables and interaction effects, and logistic regression. The clear explanation and instruction is accompanied by annotated and labeled screen shots and end-of-chapter exercises to help students apply what they have learned.

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