Statistics for Social Data Analysis

by ; ;
Edition: 4th
Format: Hardcover
Pub. Date: 2002-01-01
Publisher(s): Wadsworth Publishing
List Price: $288.95

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Summary

The fourth edition of STATISTICS FOR SOCIAL DATA ANALYSIS continues to show students how to apply statistical methods to answer research questions in various fields. Throughout the text, the authors underscore the importance of formulating substantive hypotheses before attempting to analyze quantitative data. An important aspect of this text is its realistic, hands-on approach. Actual datasets are used in most examples, helping students understand and appreciate what goes into the research process. The book focuses on the continuous-discrete distinction in considering the level at which a variable is measured. Rather than dwelling on the four conventional levels-of-measurement distinctions, the authors discuss statistics for analyzing continuous and discrete variables separately and in combination.

Table of Contents

Preface xi
I. Basic Concepts and Measures
Statistics in the Research Process
3(26)
Ideas into Research Projects
5(4)
Concepts into Propositions
9(2)
Variables into Hypotheses
11(3)
Observations into Records
14(2)
Data into Numbers
16(2)
Statistical Analysis
18(4)
The General Linear Model
22(7)
Describing Variables
29(40)
Frequency Distributions for Discrete and Continuous Variables
29(5)
Grouped and Cumulative Distributions
34(3)
Graphing Frequency Distributions
37(3)
Measures of Central Tendency
40(6)
Measures of Dispersion
46(7)
Percentiles and Quantiles
53(3)
Standardized Scores (Z Scores)
56(4)
Exploratory Data Analysis Methods for Displaying Continuous Data
60(9)
II. Statistical Inference
Making Statistical Inferences
69(42)
Drawing Inferences About Populations from Samples
69(1)
Some Basic Probability Concepts
70(3)
Chebycheff's Inequality Theorem
73(2)
The Normal Distribution
75(5)
The Central Limit Theorem
80(1)
Sample Point Estimates and Confidence Intervals
81(4)
The t Distribution
85(3)
Hypothesis Testing
88(3)
Testing Hypotheses About Single Means
91(10)
Properties of Estimators
101(1)
The Chi-Square and F Distributions
102(9)
III. Analyzing Bivariate Relationships
Analysis of Variance
111(28)
The Logic of ANOVA
111(3)
ANOVA Tables: Sums of Squares, Mean Squares, F Ratio
114(7)
Tests for Two Means
121(10)
The Correlation Ratio: Eta-Squared
131(1)
Testing Differences Among Means (Post Hoc)
132(7)
Analyzing Categoric Data
139(30)
Bivariate Crosstabulation
139(3)
Using Chi-Square to Test Significance
142(5)
Measuring Association: Q, Phi, Gamma, Tau c, Somers's dyx
147(12)
Odds and Odds Ratios
159(10)
Bivariate Regression and Correlation
169(38)
Scatterplots and Regression Lines
169(5)
Estimating a Linear Regression Equation
174(8)
R-Square and Correlation
182(5)
Significance Tests for Regression Parameters
187(7)
Standardizing Regression Coefficients
194(4)
Comparing Two Regression Equations
198(9)
IV. Multivariate Models
The Logic of Multivariate Contingency Analysis
207(28)
Controlling Additional Variables
208(5)
Controlling for a Third Variable in 2 x 2 Tables
213(10)
The Partial Correlation Coefficient
223(12)
Multiple Regression Analysis
235(52)
An Example of a Three-Variable Regression Problem
236(4)
The Three-Variable Regression Model
240(15)
Multiple Regression with K Independent Variables
255(8)
Significance Tests for Parameters
263(7)
Comparing Nested Equations
270(1)
Dummy Variable Regression: ANCOVA with Interactions
271(7)
Comparisons Across Populations
278(9)
Nonlinear and Logistic Regression
287(40)
Nonlinear Regression
288(9)
Dichotomous Dependent Variables
297(2)
The Logistic Transformation and Its Properties
299(8)
Estimating and Testing Logistic Regression Equations
307(7)
The Multinomial-Logit Model
314(13)
V. Advanced Topics
Log-Linear Analysis
327(44)
Log-Linear Models for 2 x 2 Tables
328(9)
Log-Linear Models for Three-Variable Tables
337(12)
More Complex Models
349(6)
Special Topics in Log-Linear Analysis
355(16)
Causal Models and Path Analysis
371(34)
Causal Assumptions
371(3)
Causal Diagrams
374(3)
Path Analysis
377(28)
Structural Equation Models
405(68)
Review of Correlation and Covariance
406(2)
Reliability and Validity in Measurement Theory
408(6)
Factor Analysis
414(12)
Multiple-Indicator Causal Models
426(8)
Models with Ordered Indicators
434(15)
Appendices
A. The Use of Summations
449(8)
B. Critical Values of Chi Square (table)
457(2)
C. Areas Under the Normal Curve (table)
459(6)
D. Student's t Distribution (table)
465(2)
E. F Distribution (table)
467(4)
F. Fisher's r-to-Z Transformation (table)
471(2)
Glossary of Terms 473(14)
List of Mathematical and Statistical Symbols 487(8)
Answers to Problems 495(28)
Index 523

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