Data Analysis for Social Science

Data Analysis for Social Science provides a friendly
introduction to the statistical concepts and programming skills needed
to conduct and evaluate social scientific studies. Using plain language
and assuming no prior knowledge of statistics and coding, the book
provides a step-by-step guide to analyzing real-world data with the
statistical program R for the purpose of answering a wide range of
substantive social science questions. It teaches not only how to perform
the analyses but also how to interpret results and identify strengths
and limitations. This one-of-a-kind textbook includes supplemental
materials to accommodate students with minimal knowledge of math and
clearly identifies sections with more advanced material so that readers
can skip them if they so choose.

• Analyzes real-world data using the powerful, open-sourced statistical program R, which is free for everyone to use
• Teaches how to measure, predict, and explain quantities of interest based on data
• Shows
  how to infer population characteristics using survey research, predict
  outcomes using linear models, and estimate causal effects with and
  without randomized experiments
• Assumes no prior knowledge of statistics or coding
• Specifically designed to accommodate students with a variety of math backgrounds
• Provides cheatsheets of statistical concepts and R code
• Supporting
  materials available online, including real-world datasets and the code
  to analyze them, plus—for instructor use—sample syllabi, sample lecture
  slides, additional datasets, and additional exercises with solutions