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Applied Statistics for the Social and Health Sciences (gnv64)
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Applied Statistics for the Social and Health Sciences
by Rachel A. Gordon
Routledge | May 2012 | ISBN: 9780203135297 | ePUB | 38.9 mb

Applied Statistics for the Social and Health Sciences provides graduate students in the social and health sciences with the basic skills that they need to estimate, interpret, present, and publish statistical models using contemporary standards. The book targets the social and health science branches such as human development, public health, sociology, psychology, education, and social work in which students bring a wide range of mathematical skills and have a wide range of methodological affinities. For these students, a successful course in statistics will not only offer statistical content but will also help them develop an appreciation for how statistical techniques might answer some of the research questions of interest to them.
This book is for use in a two-semester graduate course sequence covering basic univariate and bivariate statistics and regression models for nominal and ordinal outcomes, in addition to covering ordinary least squares regression.

Key features of the book 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 both SAS and Stata "side-by-side" and use of chapter exercises in which students practice programming and interpretation on the same data set and course exercises in which students can choose their own research questions and data set.

About the Author
Rachel A. Gordon is an Associate Professor in the Department of Sociology and the Institute of Government and Public Affairs at the University of Illinois at Chicago. Professor Gordon has multidisciplinary substantive and statistical training and a passion for understanding and teaching applied statistics.

CONTENTS
APPLIED STATISTICS FOR THE SOCIAL AND HEALTH SCIENCES
Preface
Acknowledgments
PART 1: GETTING STARTED
Chapter 1: Examples of Quantitative Research in the Social and Health Sciences
Chapter 2: Planning a Quantitative Research Project with Existing Data
Chapter 3: Basic Features of Statistical Packages and Data Documentation
Chapter 4: Basics of Writing Batch Programs with Statistical Packages
PART 2: BASIC DESCRIPTIVE AND INFERENTIAL STATISTICS
Chapter 5: Basic Descriptive Statistics
Chapter 6: Sample, Population and Sampling Distributions
Chapter 7: Bivariate Inferential Statistics
PART 3: ORDINARY LEAST SQUARES REGRESSION
Chapter 8: Basic Concepts of Bivariate Regression
Chapter 9: Basic Concepts of Multiple Regression
Chapter 10: Dummy Variables
Chapter 11: Interactions
Chapter 12: Nonlinear Relationships
Chapter 13: Indirect Effects and Omitted Variable Bias
Chapter 14: Outliers, Heteroskedasticity, and Multicollinearity
PART 4: THE GENERALIZED LINEAR MODEL
Chapter 15: Introduction to the Generalized Linear Model with a Continuous Outcome
Chapter 16: Dichotomous Outcomes
Chapter 17: Multi-Category Outcomes
PART 5: WRAPPING UP
Chapter 18: Roadmap to Advanced Topics
Appendices
Notes
Bibliography
Glossary/Index
 
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