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Introductory Statistics for the Behavioral Sciences, 6th Edition

ISBN: 9780471735472 | 0471735477
Edition: 6th
Format: Hardcover
Publisher: Wiley
Pub. Date: 6/1/2006

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SummaryTable of ContentsAuthor Biography
A comprehensive and user-friendly introduction to statistics-now revised and updated Introductory Statistics for the Behavioral Sciences has had a long and successful history and is a popular and well-respected statistics text. Now in its sixth edition, the text has been thoroughly revised to present all the topics students in the behavioral sciences need in a uniquely accessible format that aids in the comprehension and implementation of the statistical analyses most commonly used in the behavioral sciences. Using a continuous narrative that e... MORE
Prefacexv
Acknowledgmentsxix
Glossary of Symbolsxxi
Part I Descriptive Statistics
1(122)
... MOREIntroduction
3(20)
Why Study Statistics?
4(1)
Descriptive and Inferential Statistics
5(1)
Populations, Samples, Parameters, and Statistics
6(1)
Measurement Scales
6(2)
Independent and Dependent Variables
8(1)
Sara's Study
9(1)
Summation Notation
10(6)
Summary
16(1)
Exercises
17(3)
Thought Questions
20(1)
Computer Exercises
21(1)
Bridge to SPSS
21(2)
Frequency Distributions and Graphs
23(19)
The Purpose of Descriptive Statistics
24(1)
Regular Frequency Distributions
25(1)
Cumulative Frequency Distributions
26(1)
Grouped Frequency Distributions
27(3)
Graphic Representations
30(5)
Shapes of Frequency Distributions
35(2)
Summary
37(1)
Exercises
38(1)
Thought Questions
39(1)
Computer Exercises
40(1)
Bridge to SPSS
40(2)
Transformed Scores I: Percentiles
42(14)
Interpreting a Raw Score
43(1)
Definition of Percentile and Percentile Rank
43(1)
Computational Procedures
44(8)
Deciles, Quartiles, and the Median
52(1)
Summary
52(1)
Exercises
53(1)
Thought Questions
54(1)
Computer Exercises
54(1)
Bridge to SPSS
54(2)
Measures of Central Tendency
56(13)
Introduction
57(1)
The Mean
58(6)
The Median
64(2)
The Mode
66(1)
Summary
66(1)
Exercises
67(1)
Thought Questions
67(1)
Computer Exercises
68(1)
Bridge to SPSS
68(1)
Measures of Variability
69(16)
The Concept of Variability
70(2)
The Range
72(1)
The Semi-Interquartile Range
73(1)
The Standard Deviation and Variance
74(6)
Summary
80(2)
Exercises
82(1)
Thought Questions
83(1)
Computer Exercises
83(1)
Bridge to SPSS
84(1)
Additional Techniques for Describing Batches of Data
85(9)
Numerical Summaries
86(2)
Graphic Summaries
88(3)
Summary
91(1)
Exercises
91(1)
Thought Questions
92(1)
Computer Exercises
92(1)
Bridge to SPSS
92(2)
Transformed Scores II: z and T Scores
94(14)
Interpreting a Raw Score
95(1)
Rules for Changing X and σ
96(2)
Standard Scores (z Scores)
98(2)
T Scores and SAT Scores
100(2)
IQ Scores
102(1)
Summary
103(1)
Exercises
104(2)
Thought Questions
106(1)
Computer Exercises
106(1)
Bridge to SPSS
106(2)
The Normal Distribution
108(15)
Introduction
109(1)
Score Distributions
110(1)
Parameters of the Normal Distribution
111(1)
Tables of the Standard Normal Distribution
111(1)
Characteristics of the Normal Curve
112(1)
Illustrative Examples
113(6)
Summary
119(1)
Exercises
120(1)
Thought Questions
121(1)
Computer Exercises
121(1)
Bridge to SPSS
121(2)
Part II Basic Inferential Statistics
123(164)
Introduction to Statistical Inference
125(25)
Introduction
126(1)
The Goals of Inferential Statistics
127(1)
Sampling Distributions
128(4)
The Standard Error of the Mean
132(3)
The z Score for Sample Means
135(2)
Null Hypothesis Testing
137(7)
Assumptions Required by the Statistical Test for the Mean of a Single Population
144(1)
Summary
144(2)
Exercises
146(2)
Thought Questions
148(1)
Computer Exercises
149(1)
Bridge to SPSS
149(1)
The One-Sample t Test and Interval Estimation
150(17)
The Statistical Test for the Mean of a Single Population When σ Is Not Known: The t Distributions
151(4)
Interval Estimation
155(4)
The Standard Error of a Proportion
159(3)
Summary
162(2)
Exercises
164(1)
Thought Questions
165(1)
Computer Exercises
166(1)
Bridge to SPSS
166(1)
Testing Hypotheses about the Difference between the Means of Two Populations
167(30)
The Standard Error of the Difference
169(4)
Estimating the Standard Error of the Difference
173(1)
The t Test for Two Sample Means
174(3)
Confidence Intervals for the Difference of Two Population Means
177(2)
Using the t Test for Two Sample Means: Some General Considerations
179(2)
Measuring Size of an Effect
181(1)
The t Test for Matched Samples
182(6)
Summary
188(3)
Exercises
191(2)
Thought Questions
193(2)
Computer Exercises
195(1)
Bridge to SPSS
195(2)
Linear Correlation and Prediction
197(44)
Introduction
198(3)
Describing the Linear Relationship between Two Variables
201(9)
Interpreting the Magnitude of a Pearson r
210(2)
When Is It Important That Pearson's r be Large?
212(2)
Testing the Significance of the Correlation Coefficient
214(3)
Prediction and Linear Regression
217(8)
Measuring Prediction Error: The Standard Error of Estimate
225(3)
Summary
228(2)
Exercises
230(3)
Thought Questions
233(1)
Computer Exercises
234(1)
Bridge to SPSS
235(1)
Appendix: Equivalence of the Various Formulas for r
236(5)
The Connection between Correlation and the t Test
241(14)
Introduction
242(1)
The Point-Biserial Correlation Coefficient
243(3)
The Proportion of Variance Accounted For in Your Samples
246(1)
Estimating the Proportion of Variance Accounted For in the Population
247(2)
Summary
249(1)
Exercises
250(1)
Thought Questions
251(1)
Computer Exercises
252(1)
Bridge to SPSS
252(3)
Introduction to Power Analysis
255(32)
Introduction
256(1)
Concepts of Power Analysis
257(2)
The Test of the Mean of a Single Population
259(5)
The Significance Test of the Proportion of a Single Population
264(2)
The Significance Test of a Pearson r
266(1)
Testing the Difference between Independent Means
267(5)
Testing the Difference between the Means of Two Matched Populations
272(1)
Choosing a Value for d for a Power Analysis Involving Independent Means
273(2)
Using Power Analysis to Interpret the Results of Null Hypothesis Tests
275(2)
Summary
277(4)
Exercises
281(2)
Thought Questions
283(1)
Computer Exercises
284(1)
Bridge to SPSS
284(3)
Part III Analysis of Variance Methods
287(100)
One-Way Analysis of Variance
289(25)
Introduction
290(1)
The General Logic of ANOVA
291(4)
Computational Procedures
295(6)
Comparing the One-Way ANOVA with the t Test
301(1)
A Simplified ANOVA Formula for Equal Sample Sizes
302(3)
Effect Size for the One-Way ANOVA
305(1)
Summary
306(3)
Exercises
309(1)
Thought Questions
310(1)
Computer Exercises
311(1)
Bridge to SPSS
312(1)
Appendix: Proof That the Total Sum of Squares Is Equal to the Sum of the Between-Group and the Within-Group Sum of Squares
312(2)
Multiple Comparisons
314(18)
Introduction
315(1)
Fisher's Protected t Tests
316(3)
Tukey's Honestly Significant Difference (HSD)
319(3)
Other Multiple Comparison Procedures
322(2)
Planned and Complex Comparisons
324(3)
Summary
327(1)
Exercises
328(1)
Thought Questions
329(1)
Computer Exercises
330(1)
Bridge to SPSS
330(2)
Introduction to Factorial Design: Two-Way Analysis of Variance
332(27)
Introduction
333(1)
Computational Procedures
334(8)
The Meaning of Interaction
342(4)
Following Up a Significant Interaction
346(3)
Summary
349(3)
Exercises
352(3)
Thought Questions
355(1)
Computer Exercises
356(2)
Bridge to SPSS
358(1)
Repeated-Measures ANOVA
359(28)
Introduction
360(1)
Calculating the One-Way RM ANOVA
360(3)
Rationale for the RM ANOVA Error Term
363(2)
Assumptions of the RM ANOVA
365(2)
The RM versus RB Design: An Introduction to Issues of Experimental Design
367(4)
The Two-Way Mixed Design
371(6)
Summary
377(5)
Exercises
382(2)
Thought Questions
384(1)
Computer Exercises
384(1)
Bridge to SPSS
384(3)
Part IV Nonparametric Statistics
387(78)
Introduction to Probability and Nonparametric Methods
389(20)
Introduction
390(1)
Probability
391(3)
The Binomial Distribution
394(6)
The Sign Test for Matched Samples
400(2)
Summary
402(1)
Exercises
403(2)
Thought Questions
405(1)
Computer Exercises
406(1)
Bridge to SPSS
406(3)
Chi Square Tests
409(23)
Chi Square and Goodness of Fit: One-Variable Problems
410(4)
Chi Square as a Test of Independence: Two-Variable Problems
414(6)
Measures of Strength of Association in Two-Variable Tables
420(3)
Summary
423(2)
Exercises
425(2)
Thought Questions
427(1)
Computer Exercises
428(1)
Bridge to SPSS
429(3)
Tests for Ordinal Data
432(33)
Introduction
433(3)
The Difference between the Locations of Two Independent Samples: The Rank-Sum Test
436(4)
Differences among the Locations of Two or More Independent Samples: The Kruskal-Wallis H Test
440(4)
The Difference between the Locations of Two Matched Samples: The Wilcoxon Test
444(5)
The Relationship between Two Ranked Variables: The Spearman Rank-Order Correlation
449(3)
Summary
452(3)
Exercises
455(6)
Thought Questions
461(1)
Computer Exercises
461(1)
Bridge to SPSS
462(3)
Appendix
465(34)
Statistical Tables
467(16)
Answer Key
483(13)
Data from Sara's Experiment
496(3)
Glossary of Terms499(7)
References506(1)
Index507
Joan Welkowitz, PhD, was a Professor of Psychology at New York University. She directed the clinical program for ten years, and taught courses in methodology and statistics at both the graduate and undergraduate levels for more than twenty-five years.

Barry H. Cohen, PhD, is the Director of the master's program in psychology at New York University, where he has been teaching statistics for more than twenty years. He is the author or coauthor of two other successful statistics books also from Wiley–Explaining Psychological Statistics, Second Edition and Essentials of Statistics for the Social and Behavioral Sciences with R. Brooke Lea.

Robert B. Ewen, PhD, teaches advanced placement psychology at Gulliver Preparatory School in Miami, Florida. He previously taught statistics for eight years as an associate professor at New York University. He is also the author of a successful college text on theories of personality that is currently in its sixth edition.

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