Quantitative Data Analysis Doing Social

This book is an accessible introduction to quantitative data analysis, concentrating on the key issues facing those new to research, such as how to decide which statistical procedure is suitable, and how to interpret the subsequent results. Each chapter includes illustrative examples and a set of exercises that allows readers to test their understanding of the topic. The book, written for graduate students in the social sciences, public health, and education, offers a practical approach to making sociological sense out of a body of quantitative data. The book also will be useful to more experienced researchers who need a readily accessible handbook on quantitative methods.

Donald J. Treiman, PhD, is Distinguished Professor, Department of Sociology, University of California, Los Angeles. He was also, until recently, director of the California Center for Population Research.

Tables, Figures, Exhibits, and Boxes
Preface
The Author
Introduction
cross-Tabulations
What This Chapter Is About
Introduction to the Book via a Concrete Example
Cross-Tabulations
What This Chapter Has Shown
More on Tables
What This Chapter Is About
The Logic of Elaboration
Suppressor Variables
Additive and Interaction Effects
Direct Standardization
A Final Note on Statistical Controls Versus Experiments
What This Chapter Has Shown
Still More on Tables
What This Chapter Is About
Reorganizing Tables to Extract New Information
When to Percentage a Table "Backwards"
Cross-Tabulations in Which the Dependent Variable Is Represented by a Mean
Index of Dissimilarity
Writing About Cross-Tabulations
What This Chapter Has Shown
On the Manipulation of Data by Computer
What This Chapter Is About
Introduction
How Data Files Are Organized
Transforming Data
What This Chapter Has Shown
Appendix 4
A Doing Analysis Using Stata
Tips on Doing Analysis Using Stata
Some Particularly Useful Stata 10.0 Commands
Introduction to Correlation and Regression (Ordinary Least Squares)
What This Chapter Is About
Introduction
Quantifying the Size of a Relationship: Regression Analysis
Assessing the Strength of a Relationship: Correlation Analysis
The Relationship Between Correlation and Regression Coefficients
Factors Affecting the Size of Correlation (and Regression) Coefficients
Correlation Ratios
What This Chapter Has Shown
Introduction to Multiple Correlation and Regression (Ordinary Least Squares)
What This Chapter Is About
Introduction
A Worked Example: The Determinants of Literacy in China
Dummy Variables
A Strategy for Comparisons Across Groups
A Bayesian Alternative for Comparing Models
Independent Validation
What This Chapter Has Shown
Multiple Regression Tricks: Techniques for Handling Special Analytic Problems
What This Chapter Is About
Nonlinear Transformations
Testing the Equality of Coefficients
Trend Analysis: Testing the Assumption of Linearity
Linear Splines
Expressing Coefficients as Deviations from the Grand Mean (Multiple Classifi cation Analysis)
Other Ways of Representing Dummy Variables
Decomposing the Difference Between Two Means
What This Chapter Has Shown
Multiple Imputation of Missing Data
What This Chapter Is About
Introduction
A Worked Example: The Effect of Cultural Capital on Educational Attainment in Russia
What This Chapter Has Shown
Sample Design and Survey Estimation
What This Chapter Is About
Survey Samples
Conclusion
What This Chapter Has Shown
Regression Diagnostics
What This Chapter Is About
Introduction
A Worked
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Quantitative Data Analysis Doing Social Research to Test Ideas

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Author Biography

Table of Contents

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