ABSTRACT
Provides graduate students in the social sciences with the basic skills they need to estimate, interpret, present, and publish basic regression models using contemporary standards.
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 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.
TABLE OF CONTENTS
part |101 pages
Getting Started
chapter |26 pages
Examples of Social Science Research Using Regression Analysis
chapter |15 pages
Planning a Quantitative Research Project with Existing Data
chapter |33 pages
Basic Features of Statistical Packages and Data Documentation
chapter |25 pages
Basics of Writing Batch Programs with Statistical Packages
part |361 pages
The Regression Model
chapter |61 pages
Basic Concepts of Bivariate Regression
chapter |49 pages
Basic Concepts of Multiple Regression
chapter |63 pages
Dummy Variables
chapter |81 pages
Interactions
chapter |36 pages
Nonlinear Relationships
chapter |26 pages
Indirect Effects and Omitted Variable Bias
chapter |44 pages
Outliers, Heteroskedasticity, and Multicollinearity
part |17 pages
Wrapping Up