Applied Statistics for the Social and Health Sciences
- Available for pre-order on June 20, 2023. Item will ship after July 11, 2023
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Covering basic univariate and bivariate statistics and regression models for nominal, ordinal, and interval outcomes, Applied Statistics for the Social and Health Sciences provides graduate students in the social and health sciences with fundamental skills to estimate, interpret, and publish quantitative research using contemporary standards.
Reflecting the growing importance of ‘Big Data’ in the social and health sciences, this thoroughly revised and streamlined new edition, outlines changes in best practice in use of statistics in social and health sciences, draws upon new literatures and empirical examples, and highlights the importance of statistical programming, including coding, reproducibility, transparency, and open science.
Key features of the book include:
• interweaving the teaching of statistical concepts with examples from publicly-available social and health science data and literature excerpts
• thoroughly integrating the teaching of statistical theory with teaching of data access, processing and analysis in Stata
• recognizing debates and critiques of the origins and uses of quantitative methods
Table of Contents
Part 1: Getting ready
1. Considering examples of scholarly publications modeling social and health variables
2. Planning and starting a quantitative research project with existing data
Part 2: Describing the data
3. Graphing and summarizing individual variables
4. Introducing population estimation and hypothesis testing
5. Estimating and testing the association between two variables
Part 3: Estimating and presenting linear regression models
6. Introducing the linear regression model with two continuous variables
7. Considering nonlinearity and nonconstant variance
8. Including categorical predictor variables
9. Including more than one predictor variable in the model
10. Considering interactions among predictor variables
Part 4: Estimating and presenting generalized linear models
11. Introducing the generalized linear regression model
12. Analyzing dichotomous outcomes
13. Analyzing multi-category outcomes and offering a roadmap to additional models
Rachel A. Gordon is Associate Dean for Research and Administration and Professor of Health Studies in the College of Health and Human Sciences at Northern Illinois University, USA. Professor Gordon has multidisciplinary substantive and statistical training and a keen interest in teaching and disseminating applied statistics within the health and social sciences.
"This book is a teacher’s dream. Not only does it provide a comprehensive discussion of statistics as it is actually practiced by working researchers in the social and health sciences, it also provides detailed guidance on how to carry out such analyses using Stata, one of the best available and widely used statistical packages. Finally it provides numerous examples drawn directly from the research literature. I know of no other book like it."
Richard Campbell, Emeritus Professor of Public Health, University of Illinois at Chicago, USA
"I taught a year-long graduate level statistics course to first year sociology, education, policy analysis and demography Ph.D. students for more than 40 years. I always pieced together material from several different textbooks, software manuals, and published articles, since no one volume met the need to provide entering graduate students with appropriate content coverage at the right difficulty level. The 2nd edition of Rachel Gordon’s book, with its excellent update, meets these needs better than any other volume I have seen."
George Farkas, Distinguished Emeritus Professor of Education, University of California, Irvine, USA
"I have used the first edition of Rachel Gordon’s Applied Statistics for the Social and Health Sciences in my multidisciplinary graduate-level statistics course since I began teaching it around 5 years ago. Gordon’s ability to translate complex information into practical, real-world examples that are applicable and engaging for students across the social sciences and health disciplines has helped her textbook stand out from others. The second edition enhances this even further, bringing the material fully up-to-date with recent advances, and displaying a much-needed focus on developing students’ coding skills as well as their statistical knowledge. I anticipate Gordon’s second edition becoming a standard textbook in the field for years to come."
Jeffrey E. Stokes, Assistant Professor of Gerontology & Undergraduate Director of Aging Studies Program, University of Massachusetts Boston, USA
"I have used—and loved—the first edition of this book for nearly a decade. However, I was thrilled to see that the new edition promises to retain the rigor and clarity of purpose of the first edition, but in a more focused and streamlined package. I look forward to adopting this book for my introductory and advanced regression courses for the next decade and beyond."
Jeffrey M. Timberlake, Professor of Sociology, University of Cincinnati, USA