Quantitative Social Science & Data Analysis for Social Science

Teaching an introductory course on quantitative methods in the social sciences? We have you covered!

Is your class meant for complete beginners, with no prior experience with statistics and coding and only a minimal background in math? Check out Data Analysis for Social Science, which teaches from scratch and step-by-step the fundamentals of survey research, predictive models, and causal inference. It covers descriptive statistics, the difference-in-means estimator, simple linear regression, and multiple linear regression.

Is your class meant to teach more than just the fundamentals of social science to students with already some background in statistics and coding? Check out Quantitative Social Science, which in addition to covering the material in Data Analysis for Social Science, teaches diffs-in-diffs models, heterogeneous effects, text analysis, and regression discontinuity designs, among other things.

Both books progress by analyzing real-world data with the free and popular statistical program R for the purpose of answering a wide range of substantive social science questions. Quantitative Social Science is also available in tidyverse and in STATA.

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Quantitative Social Science Quantitative Social Science: An Introduction Kosuke Imai

An introductory textbook on data analysis and statistics written especially for students in the social sciences and allied fields
Quantitative Social Science Quantitative Social Science: An Introduction in Stata Kosuke Imai and Lori D. Bougher

The Stata edition of the groundbreaking textbook on data analysis and statistics for the social sciences and allied fields
Quantitative Social Science Quantitative Social Science: An Introduction in tidyverse Kosuke Imai and Nora Webb Williams

A tidyverse edition of the acclaimed textbook on data analysis and statistics for the social sciences and allied fields
Data Analysis for Social Science Data Analysis for Social Science: A Friendly and Practical Introduction Elena Llaudet and Kosuke Imai

An ideal textbook for an introductory course on quantitative methods for social scientists—assumes no prior knowledge of statistics or coding