Torrent details for "Data Analysis for Social Science: A Friendly and Practical Introduction" Log in to bookmark
Controls:
Language:
EnglishTotal Size:
11.65 MB
Info Hash:
f62ee5bf1831de87b4dd733556508cfa6c1294b0
Added By:
Added:
02-12-2022 14:19
Views:
195
Health:
Seeds:
2
Leechers:
0
Completed:
113
English | ISBN: 0691199426 | 2022 | 256 pages | PDF
An ideal textbook for an introductory course on quantitative methods for social scientists―assumes no prior knowledge of statistics or coding
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.
An ideal textbook for an introductory course on quantitative methods for social scientists―assumes no prior knowledge of statistics or coding
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.