Statistics Textbooks
Professor Gordon has published two textbooks that provide graduate students in the social and health sciences with the basic skills that they need to estimate, interpret, present, and publish basic regression models using contemporary standards. Key features of the books include:
•interweaving the teaching of statistical concepts with examples developed for the course from publicly-available social science data or drawn from the literature.
•thorough integration of teaching statistical theory with teaching data processing and analysis.
•teaching of Stata and use of chapter exercises in which students practice programming and interpretation on the same data set. A separate set of exercises allows students to select a data set to apply the concepts learned in each chapter to a research question of interest to them, all updated for this edition.
•interweaving the teaching of statistical concepts with examples developed for the course from publicly-available social science data or drawn from the literature.
•thorough integration of teaching statistical theory with teaching data processing and analysis.
•teaching of Stata and use of chapter exercises in which students practice programming and interpretation on the same data set. A separate set of exercises allows students to select a data set to apply the concepts learned in each chapter to a research question of interest to them, all updated for this edition.
Regression Analysis for the Social Sciences, 2nd Edition
The second edition of Regression Analysis for the Social Sciences continues to align with semester-long courses on ordinary least squares (OLS) regression. Instructors and students like the book's accessible writing style and detailed coverage of topics sometimes skimmed over in other texts (including the book's detailed treatment of categorical variables, interactions, and nonlinear relationships).
Major changes form the first edition include:
· Exclusive focus on Stata 13, and incorporation on new Stata commands, including accessible introductions to factor variables, margins and marginsplot which greatly simplify programming.
· An "at your fingertips" summary of Stata syntax located inside the front and back covers of the book.
· Movement of all Stata examples from Appendices into the chapters, so they don't require flipping to the back of the book as you read.
· Inclusion of all analysis data sets for Stata examples, making it even easier for instructors and students to replicate results.
· New literature excerpts in Chapter 1, featuring recent studies published by graduate students and new scholars, including international studies.
· All new Chapter Exercises for homework problems, drawing on the National Household Interview Survey.
From the back cover:
"The textbook achieves a seamless balance between theory and practice. It provides a gentle yet thorough review of statistical theory of regression models, all the while focusing on practical application of regression models. The textbook provides an indispensable guide for learning the complexities and mechanics of regression models and analysis in the social sciences. " Steven Prus, Sociology and Anthropology, Carleton University
"Teaching graduate statistics in the social sciences is challenging because our students arrive with such diverse levels of mathematics preparation. Rachel Gordon does an exceptional job of explaining complex statistical concepts using straightforward language and intuitive, relevant, examples. This book allows students with a range of quantitative backgrounds and comfort levels to understand and apply the material, and builds their confidence in using statistics. -Amy Kate Bailey, Sociology, University of Illinois at Chicago
"The book is distinguished for its ample use of excerpts from recent social science literature and its attention to a key range of pragmatic issues faced by investigators. The thorough integration of a major statistical package (Stata), including examples of code, links to datasets, and illustrative results, is another feature that will be widely appreciated. For instructors and students often frustrated by other texts – too simplistic or too formal, or emphasizing examples far from current social science – Gordon’s Regression Analysis for the Social Sciences will likely fit the bill." - Michael J White, Sociology, Brown University
Visit the publisher's website to order and to download supplementary materials.
Send comments or questions to Professor Gordon.
Major changes form the first edition include:
· Exclusive focus on Stata 13, and incorporation on new Stata commands, including accessible introductions to factor variables, margins and marginsplot which greatly simplify programming.
· An "at your fingertips" summary of Stata syntax located inside the front and back covers of the book.
· Movement of all Stata examples from Appendices into the chapters, so they don't require flipping to the back of the book as you read.
· Inclusion of all analysis data sets for Stata examples, making it even easier for instructors and students to replicate results.
· New literature excerpts in Chapter 1, featuring recent studies published by graduate students and new scholars, including international studies.
· All new Chapter Exercises for homework problems, drawing on the National Household Interview Survey.
From the back cover:
"The textbook achieves a seamless balance between theory and practice. It provides a gentle yet thorough review of statistical theory of regression models, all the while focusing on practical application of regression models. The textbook provides an indispensable guide for learning the complexities and mechanics of regression models and analysis in the social sciences. " Steven Prus, Sociology and Anthropology, Carleton University
"Teaching graduate statistics in the social sciences is challenging because our students arrive with such diverse levels of mathematics preparation. Rachel Gordon does an exceptional job of explaining complex statistical concepts using straightforward language and intuitive, relevant, examples. This book allows students with a range of quantitative backgrounds and comfort levels to understand and apply the material, and builds their confidence in using statistics. -Amy Kate Bailey, Sociology, University of Illinois at Chicago
"The book is distinguished for its ample use of excerpts from recent social science literature and its attention to a key range of pragmatic issues faced by investigators. The thorough integration of a major statistical package (Stata), including examples of code, links to datasets, and illustrative results, is another feature that will be widely appreciated. For instructors and students often frustrated by other texts – too simplistic or too formal, or emphasizing examples far from current social science – Gordon’s Regression Analysis for the Social Sciences will likely fit the bill." - Michael J White, Sociology, Brown University
Visit the publisher's website to order and to download supplementary materials.
Send comments or questions to Professor Gordon.
Regression Analysis for the Social Sciences
Regression Analysis for the Social Sciences is designed for a semester-long course on ordinary least squares (OLS) regression. Instructors and students like the book's accessible writing style and detailed coverage of topics sometimes skimmed over in other texts (including the book's detailed treatment of dummy variables, interactions, and nonlinear relationships).
From the back cover: "A remarkable book! Every quantitative graduate student in a social science discipline needs to master a diverse arsenal of regression-based tools. By combining clear explanation with real-world SAS and Stata examples and exercises, Gordon provides just what the doctor ordered." Greg Duncan, Education, University of California, Irvine.
Send comments or questions to Professor Gordon.
From the back cover: "A remarkable book! Every quantitative graduate student in a social science discipline needs to master a diverse arsenal of regression-based tools. By combining clear explanation with real-world SAS and Stata examples and exercises, Gordon provides just what the doctor ordered." Greg Duncan, Education, University of California, Irvine.
Send comments or questions to Professor Gordon.
Applied Statistics for the Social and Health Sciences
Applied Statistics for the Social and Health Sciences shares the same basic structure with Regression Analysis for the Social Sciences, but extends the first book in the following ways:
1. Inclusion of new literature excerpts, with broader coverage of the public health and education literatures.
2. Use of the National Health Interview Survey for chapter exercises (rather than the National Organizations Survey).
3. Inclusion of sections in many chapters that show how to implement the analysis techniques for data sets based on complex survey designs.
4. Coverage of basic univariate and bivariate descriptive and inferential statistics.
5. Coverage of the generalized linear model and maximum likelihood techniques for dichotomous outcomes and for multi-category nominal and ordinal outcomes.
From the back cover:
"True to its title, it is ideal for a wide range of social and health sciences. The examples are practical applications where students will be interested in the results. Including both SAS and Stata code and exceptionally clear help interpreting the results sets this book apart from the rest." Alan Acock, Human Development and Family Sciences, Oregon State University
"This book is a teacher's dream, perfect for an applied regression course in the health sciences. After covering introductory statistics and classical regression, it offers a sophisticated yet accessible approach to the generalized linear model, particularly with regard to logistic regression. Numerous excerpts from recent research papers complement the text nicely. I know of no book like it." Richard T. Campbell, Biostatistics and Sociology, University of Illinois at Chicago.
Visit the publisher's website to order and to download supplementary materials.
Send comments or questions to Professor Gordon.
1. Inclusion of new literature excerpts, with broader coverage of the public health and education literatures.
2. Use of the National Health Interview Survey for chapter exercises (rather than the National Organizations Survey).
3. Inclusion of sections in many chapters that show how to implement the analysis techniques for data sets based on complex survey designs.
4. Coverage of basic univariate and bivariate descriptive and inferential statistics.
5. Coverage of the generalized linear model and maximum likelihood techniques for dichotomous outcomes and for multi-category nominal and ordinal outcomes.
From the back cover:
"True to its title, it is ideal for a wide range of social and health sciences. The examples are practical applications where students will be interested in the results. Including both SAS and Stata code and exceptionally clear help interpreting the results sets this book apart from the rest." Alan Acock, Human Development and Family Sciences, Oregon State University
"This book is a teacher's dream, perfect for an applied regression course in the health sciences. After covering introductory statistics and classical regression, it offers a sophisticated yet accessible approach to the generalized linear model, particularly with regard to logistic regression. Numerous excerpts from recent research papers complement the text nicely. I know of no book like it." Richard T. Campbell, Biostatistics and Sociology, University of Illinois at Chicago.
Visit the publisher's website to order and to download supplementary materials.
Send comments or questions to Professor Gordon.
Courses
In the UIC sociology department, Professor Gordon taught graduate statistics for over a decade and periodically taught advanced statistics' courses. Gordon also taught substantive courses in sociology and the honors college about children youth, and families, education, and social policy, such as Sociology of the Family, Contexts of Social Inequality , and Social Inequality and Mental Health.