An ideal textbook for an introductory course on quantitative methods for social scientists 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. A more accessible version of Kosuke Imai's Quantitative Social Science 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
They include Jill Dolan, Chris Eisgruber, Dave Lee, Nolan McCarty, Debbie Prentice, and Val Smith. ... I also thank Neal Beck, Andy Hall, Ryan Moore, and Marc Ratkovic for their comments on earlier versions of the manuscript.
In addition to updating all the tables and examples with new data, the Second Edition has replaced the section on SPSS with three new sets of exercises at the end of each chapter: Chapter Exercises for students complete during their reading ...
Applications in R G. David Garson. ROUTLEDGE R Data Analytics for the Social Sciences Applications in R G. David Garson Data Analytics for the Social Sciences Data Analytics for the.
The book provides practical guidance on combining methods and tools from computer science, statistics, and social science.
Statistical analysis is common in the social sciences, and among the more popular programs is R. This book provides a foundation for undergraduate and graduate students in the social sciences on how to use R to manage, visualize, and ...
Abridged Contents PART ONE: HOW TO PREPARE DATA FOR ANALYSIS\PART TWO: HOW TO PREPARE VARIABLE FOR ANALYSIS\PART THREE: HOW TO REDUCE THE AMOUNT OF DATA TO ANALYZE\PART FOUR: HOW AND WHEN TO GENERALIZE\PART FIVE: HOW TO ANALYZE A SINGLE ...
Packed with global, interdisciplinary examples that ground statistical theory and concepts in real-world situations, it shows students not only how to apply newfound knowledge using IBM SPSS Statistics, but also...
Korn, E. L., & Graubard, B. I. (1999). Analysis of health surveys. New York, NY: Wiley. Kreager, D. A., & Staff, J. (2009). The sexual double standard and adolescent peer acceptance. Social Psychology Quarterly, 72, 143–164.
Optional technology use is paired with the core elements of the course, making this text a pragmatic and engaging introduction to the practice of social statistics.
Optional technology use is paired with the core elements of the course, making this text a pragmatic and engaging introduction to the practice of social statistics. Note: MySearchLab does not come automatically packaged with this text.