Table of contents for Statistics for the social sciences / R. Mark Sirkin.

Bibliographic record and links to related information available from the Library of Congress catalog.

Note: Contents data are machine generated based on pre-publication provided by the publisher. Contents may have variations from the printed book or be incomplete or contain other coding.


Counter
[Contents]
Contents
Preface
Acknowledgments
1. How We Reason
Key Concepts
Prologue and Introduction
Setting the Stage
Science
The Scientific Method
Testing Hypotheses
From Hypotheses to Theories
Types of Relationships
Association and Causation
The Unit of Analysis
Conclusion
Exercises
2. Levels of Measurement and Forms of Data
Key Concepts
Prologue and Introduction
Measurement
Nominal Level of Measurement
Ordinal Level of Measurement
Likert Scales
Scores Versus Frequencies
Interval and Ratio Levels of Measurement
Tables Containing Nominal Level of Measurement
Variables
Conclusion
Exercises
3. Defining Variables
Key Concepts
Prologue and Introduction
Gathering the Data
Operational Definitions
Index and Scale Construction
Validity
Reliability
Conclusion
Exercises
4. Measuring Central Tendency
Key Concepts
Prologue and Introduction
Central Tendency
The Mean
The Median
Using Central Tendency
The Mode
Interpreting Graphs
Central Tendency and Levels of Measurement
Skewness
Other Graphic Representations
Conclusion
Summary of Major Formulas
Exercises
5. Measuring Dispersion
Key Concepts
Prologue and Introduction
Visualizing Dispersion
The Range
The Mean Deviation
The Variance and Standard Deviation
The Computational Formulas for Variance and Standard Deviation
Variance and Standard Deviation for Data in Frequency Distributions
Conclusion
Summary of Major Formulas
Exercises
6. Constructing and Interpreting Contingency Tables
Key Concepts
Prologue and Introduction
Contingency Tables
Regrouping Variables
Generating Percentages
Interpreting
Controlling for a Third Variable
Partial Tables
Causal Models
Computer Applications
SPSS
SAS
Conclusion
Exercises
7. Statistical Inference and Tests of Significance
Key Concepts
Prologue and Introduction
What Is Statistical Inference?
Random Samples
Comparing Means
The Test Statistic
Probabilities
Decision Making
Directional Versus Nondirectional Alternative
Hypotheses (One-Tailed Versus Two-Tailed Tests)
Conclusion
Summary of Major Formulas
Exercises
8. Probability Distributions and One-Sample Z and t Tests
Key Concepts
Prologue and Introduction
Normal Distributions
The One-Sample z test for Statistical Significance
The Central Limit Theorem
The Normality Assumption
The One-Sample t Test
Degrees of Freedom
The t Table
An Alternative t Formula
A z Test for Proportions
Interval Estimation
Confidence Intervals for Proportions
More on Probability
Permutations and Combinations
Conclusion
Summary of Major Formulas
Exercises
9. Two-Sample t Tests
Key Concepts
Prologue and Introduction
Independent Samples Versus Dependent Samples
The Two-Sample t Test for Independently Drawn Samples
Adjustments for Sigma-Hat Squared (? 2)
Interpreting a Computer-Generated t Test
Computer Applications
Independent Sample Tests
SPSS
SAS
Excel
Dependent Sample Tests
SPSS
SAS
Excel
The Two-Sample t Test for Dependent Samples
Statistical Significance Versus Research
Significance
Statistical Power
Conclusion
Summary of Major Formulas
Exercises
10. One-Way Analysis of Variance
Key Concepts
Prologue and Introduction
How Analysis of Variance Is Used
Analysis of Variance in Experimental Situations
F: An Intuitive Approach
ANOVA Terminology
The ANOVA Procedure
Comparing F with t
Analysis of Variance With Experimental Data
Post Hoc Testing
Computer Applications
SPSS
SAS
Excel
Two-way Analysis of Variance
Conclusion
Summary of Major Formulas
Exercises
11. Measuring Association in Contingency Tables
Key Concepts
Prologue and Introduction
Measures for Two-by-Two Tables
Measures
Curvilinearity for n-by-n
Other Measures of Association
Interpreting an Association Matrix
Conclusion
Summary of Major Formulas
Exercises
12. The Chi-Square Test
Key Concepts
Prologue and Introduction
The Context for the Chi-Square Test
Observed Versus Expected Frequencies
Using the Table of Critical Value of Chi-Square
Calculating the Chi-Square Value
Yates? Correction
Validity of Chi-Square
Directional Alternative Hypotheses
Testing Significance of Association Measures
Chi-square and Phi
Computer Applications
SPSS
SAS
Conclusion
Summary of Major Formulas
Exercises
13. Correlation and Regression Analysis
Key Concepts
Prologue and Introduction
The Setting
Cartesian Coordinates
The Concept of Linearity
Linear Equations
Linear Regression
Computer Applications
SPSS
SAS
Excel
Correlation Measures for Analysis of Variance
Conclusion
Summary of Major Formulas
Exercises
14. Additional Aspects of Correlation and
Regression Analysis
Key Concepts
Prologue and Introduction
Statistical Significance for r and b
Significance of r
Partial Correlations and Causal Models
Multiple Correlation and The Coefficient of Multiple Determination
Multiple Regression
The Standardized Partial Regression Slope
Using a Regression Printout
Stepwise Multiple Regression
Computer Applications
Partial Correlations: SPSS
Partial Correlations: Other Programs
Multiple Regression: SPSS
Multiple Regression: SAS
Multiple Regression: Excel
Stepwise Multiple Regression: SPSS
Stepwise Multiple Regression: SAS
Conclusion
Summary of Major Formulas
Exercises
Appendix 1: Proportions of Area Under Standard Normal Curve
Appendix 2: Distribution of t
Appendix 3: Critical Values of F for p = .05
Appendix 4: Critical Values of Chi-Square
Appendix 5: Critical Values of the Correlation Coefficient
Answers to Selected Exercises
Index
About the Author

Library of Congress Subject Headings for this publication:

Social sciences -- Statistical methods.
Statistics.