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.