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Summary:

"Data analysis has become a necessary skill across the social sciences, and recent advancements in computing power have made knowledge of programming an essential component. Yet most data science books are intimidating and overwhelming to a non-specialist audience, including most undergraduates. This book will be a shorter, more focused and accessible version of Kosuke Imai's Quantitative Social Science book, which was published by Princeton in 2018 and has been adopted widely in graduate level courses of the same title. This book uses the same innovative approach as Quantitative Social Science , using real data and 'R' to answer a wide range of social science questions. It assumes no prior knowledge of statistics or coding. It starts with straightforward, simple data analysis and culminates with multivariate linear regression models, focusing more on the intuition of how the math works rather than the math itself. The book makes extensive use of data visualizations, diagrams, pictures, cartoons, etc., to help students understand and recall complex concepts, provides an easy to follow, step-by-step template of how to conduct data analysis from beginning to end, and will be accompanied by supplemental materials in the appendix and online for both students and instructors"-- [Provided by publisher]

Author/Creator:

Llaudet, Elena, 1978- , author

Contributors:

Imai, Kosuke , author

Languages:

English

Language Notes:

Item content: English

Main Work:

Data analysis for social science: a friendly and practical introduction [by Llaudet, E.]

Subjects:

Social sciences — Statistical methods

Social sciences — Data processing

Social sciences — Methodology

Social sciences

General Notes:

Includes indexes.

Physical Description:

xii, 238 pages : illustrations ; 26 cm

Physical Characteristics:

illustration

Call Numbers:

HA29 .L835339 2023

ISBNs:

9780691199436 (paperback, alk. paper)
0691199434 (paperback, alk. paper)
9780691199429 (hardback, alk. paper)
0691199426 (hardback, alk. paper)
9780691229348 (ebook) [Invalid]

Library of Congress Control Numbers:

2022030106

OCLC Numbers:

1294287547