This book provides a first-class, reliable guide to the basic issues in data analysis, such as the construction of variables, the characterization of distributions and the notions of inference. Scholars and students can turn to it for teaching and applied needs with confidence. No other book provides a better one-stop survey of the field of data analysis. In 30 specially commissioned chapters the editors aim to encourage readers to develop an appreciation of the range of analytic options available, so they can choose a research problem and then develop a suitable approach to data analysis.This book provides a first-class, reliable guide to the basic issues in data analysis, such as the construction of variables, the characterization of distributions and the notions of inference. Scholars and students can turn to it for teaching and applied needs with confidence. No other book provides a better one-stop survey of the field of data analysis. In 30 specially commissioned chapters the editors aim to encourage readers to develop an appreciation of the range of analytic options available, so they can choose a research problem and then develop a suitable approach to data analysis.Introduction: Common Threads among Techniques of Data Analysis - Melissa Hardy and Alan Bryman PART ONE: FOUNDATIONS Constructing Variables - Alan Bryman and Duncan Cramer Summarizing Distributions - Melissa Hardy Inference - Lawrence Hazelrigg Strategies for Analysis of Incomplete Data - Mortaza Jamshidian Feminist Issues in Data Analysis - Mary Maynard Historical Analysis - Dennis Smith PART TWO: THE GENERAL LINEAR MODEL AND EXTENSIONS Multiple Regression Analysis - Ross M. Stolzenberg Incorporating Categorical Information into Regression Models: The Utility of Dummy Variables - Melissa Hardy and John Reynolds Analyzing Contingent Effects in Regression Models - James Jaccardl3