Statistics for the Behavioral Sciences,9780534569259

Statistics for the Behavioral Sciences

by ;
Edition: 4th
ISBN13: 9780534569259
ISBN10: 0534569250
Format: Hardcover
Pub. Date: 2001-10-29
Publisher(s): Wadsworth Publishing
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Summary

Part I: STATISTICAL PRELIMINARIES. 1. Introduction and Mathematical Preliminaries. 2. Frequency and Probability Distributions. 3. Measures of Central Tendency and Variability. 4. Percentiles, Percentile Ranks, Standard Scores, and the Normal Distribution. 5. Pearson Correlation and Regression: Descriptive Aspects. 6. Probability. 7. Estimation and Sampling Distributions. 8. Hypothesis Testing: Inferences About a Single Mean. Part II: THE ANALYSIS OF BIVARIATE RELATIONSHIPS. 9. Research Design and Statistical Preliminaries for Analyzing Bivariate Relationships. 10. Independent Groups t Test. 11. Correlated Groups t Test. 12. One-Way Between-Subjects Analysis of Variance. 13. One-Way Repeated Measures Analysis of Variance. 14. Pearson Correlation and Regression: Inferential Aspects. 15. Chi-Square Test. 16. Nonparametric Statistics. Part III: ADDITIONAL TOPICS. 17. Two-Way Between-Subjects Analysis of Variance. 18. Overview and Extension: Selecting the Appropriate Statistical Test for Analyzing Bivariate Relationships and Procedures for More Complex Designs.

Table of Contents

Preface xv
To the Student xxi
Part 1 Statistical Preliminaries 1(238)
Introduction and Mathematical Preliminaries
2(32)
The Study of Statistics
2(2)
Research in the Behavioral Sciences
4(1)
Variables
5(1)
Measurement
6(8)
Discrete and Continuous Variables
14(2)
Populations and Samples
16(2)
Biased Sampling
17(1)
Descriptive and Inferential Statistics
18(1)
The Concept of Probability
19(1)
Mathematical Preliminaries: A Review
20(8)
Statistics and Computers
28(6)
Summary
29(5)
Frequency and Probability Distributions
34(33)
Frequency Distributions for Quantitative Variables: Ungrouped Scores
34(4)
Frequency Distributions for Quantitative Variables: Grouped Scores
38(3)
Frequency Distributions for Qualitative Variables
41(1)
Outliers
42(1)
Frequency Graphs
43(8)
Misleading Graphs
51(1)
Graphs of Relative Frequencies, Percentages, Cumulative Frequencies, and Cumulative Relative Frequencies
52(1)
Probability Distributions
53(3)
Empirical and Theoretical Distributions
56(1)
Method of Presentation
57(2)
Examples from the Literature
59(8)
Summary
63(4)
Measures of Central Tendency and Variability
67(33)
Measures of Central Tendency for Quantitative Variables
68(10)
Measures of Variability for Quantitative Variables
78(5)
Computational Formula for the Sum of Squares
83(2)
Relationship Between Central Tendency and Variability
85(1)
Graphs of Central Tendency and Variability
86(3)
Measures of Central Tendency and Variability for Qualitative Variables
89(1)
Skewness and Kurtosis
90(1)
Sample Versus Population Notation
91(1)
Method of Presentation
91(1)
Example from the Literature
92(8)
Summary
95(5)
Percentiles, Percentile Ranks, Standard Scores, and the Normal Distribution
100(25)
Percentiles and Percentile Ranks
101(4)
Standard Scores
105(4)
Standard Scores and the Normal Distribution
109(4)
Standard Scores and the Shape of the Distribution
113(1)
Method of Presentation
113(12)
Summary
120(1)
The Normal Distribution Formula
121(4)
Pearson Correlation and Regression: Descriptive Aspects
125(32)
Use of Pearson Correlation
125(1)
The Linear Model
126(4)
The Pearson Correlation Coefficient
130(8)
Correlation and Causation
138(1)
Interpreting the Magnitude of a Correlation Coefficient
139(1)
Regression
140(5)
Additional Issues Associated with the Use of Correlation and Regression
145(12)
Summary
153(4)
Probability
157(24)
Probabilities of Simple Events
159(1)
Conditional Probabilities
160(1)
Joint Probabilities
161(1)
Adding Probabilities
162(1)
Relationships Among Probabilities
162(2)
Sampling with Versus Without Replacement
164(2)
Beliefs and Probability Theory
165(1)
Counting Rules
166(3)
The Binomial Expression
169(12)
Summary
176(5)
Estimation and Sampling Distributions
181(24)
Finite Versus Infinite Populations
181(1)
Estimation of the Population Mean
182(2)
Estimation of the Population Variance and Standard Deviation
184(3)
Degrees of Freedom
187(1)
Sampling Distribution of the Mean and the Central Limit Theorem
188(9)
Polls and Random Samples
191(6)
Types of Sampling Distributions
197(8)
Summary
202(3)
Hypothesis Testing: Inferences About a Single Mean
205(34)
A Simple Analogy for Principles of Hypothesis Testing
205(1)
Statistical Inference and the Normal Distribution: The One-Sample z Test
206(4)
Defining Expected and Unexpected Results
210(1)
Failing to Reject Versus Accepting the Null Hypothesis
211(1)
Type I and Type II Errors
212(2)
Effects of Alpha and Sample Size on the Power of Statistical Tests
214(2)
Statistical and Real-World Significance
216(1)
Directional Versus Nondirectional Tests
216(3)
Statistical Inference Using Estimated Standard Errors: The One-Sample t Test
219(6)
Confidence Intervals
225(4)
Method of Presentation
229(2)
Examples from the Literature
231(8)
Summary
233(6)
Part 2 The Analysis of Bivariate Relationships 239(256)
Research Design and Statistical Preliminaries for Analyzing Bivariate Relationships
240(19)
Principles of Research Design: Statistical Implications
240(11)
Confounding and Disturbance Variables
247(4)
Selecting the Appropriate Statistical Test to Analyze a Relationship: A Preview
251(8)
Summary
255(4)
Independent Groups t Test
259(43)
Use of the Independent Groups t Test
259(2)
Inference of a Relationship Using the Independent Groups t Test
261(10)
Strength of the Relationship
271(9)
Nature of the Relationship
280(1)
Methodological Considerations
281(1)
Numerical Example
281(3)
Planning an Investigation Using the Independent Groups t Test
284(2)
Method of Presentation
286(1)
Examples from the Literature
287(15)
Summary
294(8)
Correlated Groups t Test
302(27)
Use of the Correlated Groups t Test
302(1)
Inference of a Relationship Using the Correlated Groups t Test
303(5)
Strength of the Relationship
308(3)
Nature of the Relationship
311(1)
Methodological Considerations
311(1)
Power of Correlated Groups Versus Independent Groups t Tests
312(2)
Numerical Example
314(2)
Planning an Investigation Using the Correlated Groups t Test
316(1)
Method of Presentation
317(1)
Examples from the Literature
318(11)
Summary
321(1)
Computational Procedures for the Nullified Score Approach
322(7)
One-Way Between-Subjects Analysis of Variance
329(40)
Use of One-Way Between-Subjects Analysis of Variance
329(1)
Inference of a Relationship Using One-Way Between-Subjects Analysis of Variance
330(14)
Relationship of the F Test to the t Test
344(1)
Strength of the Relationship
344(1)
Nature of the Relationship
345(4)
Unstandardized Effect Sizes and Confidence Intervals
349(1)
Methodological Considerations
350(1)
Numerical Example
350(4)
Planning an Investigation Using One-Way Between-Subjects Analysis of Variance
354(1)
Method of Presentation
354(2)
Examples from the Literature
356(13)
Summary
360(1)
Rationale for the Degrees of Freedom
361(8)
One-Way Repeated Measures Analysis of Variance
369(33)
Use of One-Way Repeated Measures Analysis of Variance
369(2)
Inference of a Relationship Using One-Way Repeated Measures Analysis of Variance
371(9)
Strength of the Relationship
380(1)
Nature of the Relationship
381(2)
Unstandardized Effect Size and Confidence Intervals
383(1)
Methodological Considerations
383(2)
Numerical Example
385(3)
Planning an Investigation Using One-Way Repeated Measures Analysis of Variance
388(1)
Method of Presentation
389(1)
Examples from the Literature
390(12)
Summary
395(1)
Determining the Nature of the Relationship Under Sphericity Violations
395(7)
Pearson Correlation and Regression: Inferential Aspects
402(31)
Use of Pearson Correlation
402(1)
Inference of a Relationship Using Pearson Correlation
403(4)
Strength of the Relationship
407(1)
Confidence Intervals for the Correlation Coefficient
407(1)
Nature of the Relationship
408(1)
Planning an Investigation Using Pearson Correlation
408(1)
Method of Presentation for Pearson Correlation
408(1)
Examples from the Literature
409(2)
Regression
411(3)
Numerical Example
414(4)
Method of Presentation for Regression
418(15)
Summary
423(1)
Testing Null Hypotheses Other Than p = 0
423(2)
Confidence Intervals for the Correlation Coefficient
425(8)
Chi-Square Test
433(30)
Use of the Chi-Square Test
433(1)
Two-Way Contingency Tables
434(1)
Chi-Square Tests of Independence and Homogeneity
435(1)
Inference of a Relationship Using the Chi-Square Test
435(6)
2 x 2 Tables
441(1)
Strength of the Relationship
442(1)
Nature of the Relationship
443(1)
Methodological Considerations
444(1)
Numerical Example
445(1)
Use of Quantitative Variables in the Chi-Square Test
446(1)
Planning an Investigation Using the Chi-Square Test
447(1)
Method of Presentation
448(1)
Examples from the Literature
449(2)
Chi-Square Goodness-of-Fit Test
451(12)
Summary
455(1)
Determining the Nature of the Relationship Using a Modified Bonferroni Procedure
456(7)
Nonparametric Statistics
463(32)
Rank Scores
464(2)
Nonparametric Statistics and Outliers
466(1)
Analysis of Ranked Data Using Parametric Formulas
467(1)
Rank Tests for Two Independent Groups
467(4)
Rank Test for Two Correlated Groups
471(3)
Rank Test for Three or More Independent Groups
474(3)
Rank Test for Three or More Correlated Groups
477(3)
Rank Test for Correlation
480(3)
Examples from the Literature
483(12)
Summary
486(1)
Corrections for Ties for Nonparametric Rank Tests
486(9)
Part 3 Additional Topics 495(64)
Two-Way Between-Subjects Analysis of Variance
496(48)
Factorial Designs
497(1)
Use of Two-Way Between-Subjects Analysis of Variance
498(1)
The Concepts of Main Effects and Interactions
499(7)
Inference of Relationships Using Two-Way Between-Subjects Analysis of Variance
506(8)
Strength of the Relationships
514(1)
Nature of the Relationships
515(3)
Methodological Considerations
518(1)
Numerical Example
518(8)
Unequal Sample Sizes
526(1)
Planning an Investigation Using Two-Way Between-Subjects Analysis of Variance
527(2)
Method of Presentation
529(2)
Examples from the Literature
531(13)
Summary
536(8)
Overview and Extension: Selecting the Appropriate Statistical Test for Analyzing Bivariate Relationships and Procedures for More Complex Designs
544(15)
Selecting the Appropriate Statistical Test for Analyzing Bivariate Relationships
544(1)
Case I: The Relationship Between Two Qualitative Variables
545(1)
Case II: The Relationship Between a Qualitative Independent Variable and a Quantitative Dependent Variable
545(4)
Case III: The Relationship Between a Quantitative Independent Variable and a Qualitative Dependent Variable
549(1)
Case IV: The Relationship Between Two Quantitative Variables
549(1)
Procedures for More Complex Designs
550(3)
Alternative Approaches to Null Hypothesis Testing
553(6)
Summary
554(5)
Appendix A Table of Random Numbers 559(3)
Appendix B Proportions of Scores in a Normal Distribution 562(10)
Appendix C Factorials 572(1)
Appendix D Critical Values for the Distribution 573(2)
Appendix E Power and Sample Size 575(24)
Appendix F Critical Values for the F Distribution 599(4)
Appendix G Studentized Range Values (q) 603(3)
Appendix H Critical Values for Pearson r 606(2)
Appendix I Fisher's Transformation of Pearson r (r') 608(2)
Appendix J Critical Values for the Chi-Square Distribution 610(2)
Appendix K Critical Values for the Mann--Whitney U Test 612(3)
Appendix L Critical Values for the Wilcoxon Signed-Rank Test 615(2)
Appendix M Critical Values for Spearman r 617(2)
Appendix N Formulas for Unbiased Estimators of Proportion of Explained Variance 619(1)
Answers to Selected Exercises 620(19)
Glossary of Major Symbols 639(5)
References 644(7)
Index 651(7)
Credits 658

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