Data Analysis for Social Science: A Friendly and Practical Introduction – PDF

# Data Analysis for Social Science: A Friendly and Practical Introduction – eBook

The ebook “Data Analysis for Social Science” is perfect for beginners and assumes no prior knowledge of statistics or coding, and only minimal knowledge of math.

This ebook introduces statistical concepts and programming skills necessary for conducting and evaluating social scientific studies. It uses simple language and assumes no prior knowledge of statistics and coding. The book teaches the basics of survey research, predictive models, and causal inference while analyzing data from published studies using the statistical program R. It focuses not only on performing data analyses but also on interpreting the results and identifying the strengths and limitations of the analyses.

**Key Features:**
– The book progresses by teaching how to solve different types of problems, introducing methods as needed, including estimating causal effects with randomized experiments, visualizing and summarizing data, inferring population characteristics, predicting outcomes, estimating causal effects with observational data, and generalizing from sample to population.
– It deviates from traditional statistics textbooks by starting with estimating causal effects with randomized experiments and postponing probability and statistical inference discussions until the end. This order showcases from the beginning how data analysis can answer interesting questions, reserving more complex concepts for later chapters.
– The ebook provides a step-by-step guide to analyzing real-world data using the open-source statistical program R. Datasets are available on the book’s website for readers to follow along with the exercises on their own computers.
– It is specifically designed to accommodate students with various math backgrounds. It includes additional resources for students with minimal math knowledge and clearly identifies sections with more advanced material for readers to skip if desired.
– It offers cheat sheets of statistical concepts and R code.
– Instructor materials, such as sample syllabi, lecture slides, and additional exercises with solutions using real-world datasets, are available upon request.
– For a more advanced introduction, consider *Quantitative Social Science* by Kosuke Imai, which covers the material in *Data Analysis for Social Science*, as well as teaching diffs-in-diffs models, heterogeneous effects, text analysis, and regression discontinuity designs, among other things.

ISBNs: 978-0691199429, 978-0691229348, 978-0691199436

NOTE: This sale only includes the ebook *Data Analysis for Social Science: A Friendly and Practical Introduction in PDF* for download. No access codes are included.