Quantitative Social Science : An Introduction in Tidyverse

Kosuke Imai

ISBN 10: 0691222282 / ISBN 13: 9780691222288

Published by Princeton University Press Aug 2022, 2022

About this Item

Neuware - 'This 'translation' of Imai's Quantiative Social Science makes the book adoptable in courses that use tidyverse. Tidyverse is a 'dialect' of R--that is, it is a set of R packages that make data science work more user-friendly. Many instructors find tidyverse much easier to teach and are increasingly using this in the classroom setting'.

Seller Inventory # 9780691222288

Bibliographic Details

• Title: Quantitative Social Science : An Introduction in Tidyverse
• Publisher: Princeton University Press Aug 2022
• Publication Date: 2022
• Language: English
• ISBN 10: 0691222282
• ISBN 13: 9780691222288
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 250W x 173H x 29D millimeters 250 millimeters width by 173 millimeters height by 29 millimeters depth
• Weight: 866 grams

About this title

Synopsis

A tidyverse edition of the acclaimed textbook on data analysis and statistics for the social sciences and allied fields

Quantitative analysis is an essential skill for social science research, yet students in the social sciences and related areas typically receive little training in it. Quantitative Social Science is a practical introduction to data analysis and statistics written especially for undergraduates and beginning graduate students in the social sciences and allied fields, including business, economics, education, political science, psychology, sociology, public policy, and data science. Proven in classrooms around the world, this one-of-a-kind textbook engages directly with empirical analysis, showing students how to analyze and interpret data using the tidyverse family of R packages. Data sets taken directly from leading quantitative social science research illustrate how to use data analysis to answer important questions about society and human behavior.

• Emphasizes hands-on learning, not paper-and-pencil statistics
• Includes data sets from actual research for students to test their skills on
• Covers data analysis concepts such as causality, measurement, and prediction, as well as probability and statistical tools
• Features a wealth of supplementary exercises, including additional data analysis exercises and programming exercises
• Offers a solid foundation for further study
• Comes with additional course materials online, including notes, sample code, exercises and problem sets with solutions, and lecture slides

About the Author

Kosuke Imai is Professor of Government and of Statistics at Harvard University. Nora Webb Williams is Assistant Professor of Political Science at the University of Illinois, Urbana-Champaign.