An Introduction to Political and Social Data Analysis (With R) provides students with an accessible overview of practical data analysis while also providing a gentle introduction to the R programming environment. Author Thomas M. Holbrook patiently explains each step in statistical analysis with R, avoiding complicated tools or packages.
An Introduction to Political and Social Data Analysis (With R) provides students with an accessible overview of practical data analysis while also providing a gentle introduction to the R programming environment. Author Thomas M. Holbrook patiently explains each step in statistical analysis with R, avoiding complicated tools or packages.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Thomas Holbrook is Emeritus Professor at the University of Wisconsin-Milwaukee, where he was a Distinguished Professor and the Wilder Crane Professor of Government in the political science department. He is a former editor of American Politics Research and the author of Do Campaigns Matter (Sage, 1996), Altered States (Oxford, 2016), and dozens of articles on various aspects of voting behavior and elections in the United States, most recently focusing on local politics. Professor Holbrook has taught undergraduate courses on data analysis and survey research for the past three decades and has integrated R into his data analysis courses for the past several years.
Inhaltsangabe
Introduction to Research and Data Using R to Do Data Analysis Frequencies and Basic Graphs Data Preparation Measures of Central Tendency Measures of Dispersion Probability Sampling and Inference Hypothesis Testing Hypothesis Testing with Two Groups Hypothesis Testing With Multiple Groups (ANOVA) Hypothesis Testing with Non-Numeric Variables (Crosstabs) Measures of Association Correlation and Scatterplots Simple Regression Multiple Regression Advanced Regression Topics Regression Assumptions
Introduction to Research and Data Using R to Do Data Analysis Frequencies and Basic Graphs Data Preparation Measures of Central Tendency Measures of Dispersion Probability Sampling and Inference Hypothesis Testing Hypothesis Testing with Two Groups Hypothesis Testing With Multiple Groups (ANOVA) Hypothesis Testing with Non-Numeric Variables (Crosstabs) Measures of Association Correlation and Scatterplots Simple Regression Multiple Regression Advanced Regression Topics Regression Assumptions
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