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Statistics for the Behavioral Sciences 3rd Revised edition [Kõva köide]

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  • Formaat: Hardback, 816 pages, kõrgus x laius: 254x203 mm
  • Ilmumisaeg: 14-Oct-2017
  • Kirjastus: SAGE Publications (USA)
  • ISBN-10: 1506386253
  • ISBN-13: 9781506386256
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Statistics for the Behavioral Sciences 3rd Revised editionSuurem pilt
  • Formaat: Hardback, 816 pages, kõrgus x laius: 254x203 mm
  • Ilmumisaeg: 14-Oct-2017
  • Kirjastus: SAGE Publications (USA)
  • ISBN-10: 1506386253
  • ISBN-13: 9781506386256
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781506386256.html
Märksõnad:

The engaging Third Edition of Statistics for the Behavioral Sciences shows students that statistics can be understandable, interesting, and relevant to their daily lives. Using a conversational tone, award-winning teacher and author Gregory J. Privitera speaks to the reader as researcher when covering statistical theory, computation, and application. Robust pedagogy allows students to continually check their comprehension and hone their skills when working through carefully developed problems and exercises that include current research and seamless integration of SPSS. This edition will not only prepare students to be lab-ready, but also give them the confidence to use statistics to summarize data and make decisions about behavior. 

About the Author xxiii
Acknowledgments xxv
Preface to the Instructor xxvii
To the Student-How to Use SPSS With This Book xxxvii
Part I. Introduction And Descriptive Statistics 1(136)
Chapter 1 Introduction to Statistics
2(30)
1.1 The Use of Statistics in Science
3(1)
1.2 Descriptive and Inferential Statistics
4(4)
Descriptive Statistics
5(1)
Inferential Statistics
6(2)
Making Sense: Populations and Samples
7(1)
1.3 Research Methods and Statistics
8(7)
Experimental Method
9(3)
Making Sense: Experimental and Control Groups
12(1)
Quasi-Experimental Method
12(1)
Correlational Method
13(2)
1.4 Scales of Measurement
15(4)
Nominal Scales
16(1)
Ordinal Scales
16(1)
Interval Scales
17(1)
Ratio Scales
18(1)
1.5 Types of Variables for Which Data Are Measured
19(3)
Continuous and Discrete Variables
20(1)
Quantitative and Qualitative Variables
20(2)
1.6 Research in Focus: Evaluating Data and Scales of Measurement
22(1)
1.7 SPSS in Focus: Entering and Defining Variables
23(3)
Chapter Summary
26(1)
Key Terms
27(1)
End-of-Chapter Problems
28(1)
Factual Problems
28(1)
Concept and Application Problems
28(2)
Problems in Research
30(2)
Chapter 2 Summarizing Data: Frequency Distributions in Tables and Graphs
32(44)
2.1 Why Summarize Data?
33(1)
2.2 Frequency Distributions for Grouped Data
34(10)
Simple Frequency Distributions
35(4)
Cumulative Frequency
39(2)
Relative Frequency
41(1)
Relative Percent
41(1)
Cumulative Relative Frequency and Cumulative Percent
42(2)
2.3 Identifying Percentile Points and Percentile Ranks
44(2)
2.4 SPSS in Focus: Frequency Distributions for Quantitative Data
46(3)
2.5 Frequency Distributions for Ungrouped Data
49(1)
2.6 Research in Focus: Summarizing Demographic Information
50(1)
2.7 SPSS in Focus: Frequency Distributions for Categorical Data
51(1)
2.8 Pictorial Frequency Distributions
52(2)
2.9 Graphing Distributions: Continuous Data
54(5)
Histograms
54(1)
Frequency Polygons
55(1)
Ogives
56(1)
Stem-and-Leaf Displays
57(2)
2.10 Graphing Distributions: Discrete and Categorical Data
59(5)
Bar Charts
60(1)
Pie Charts
61(17)
Making Sense: Deception Due to the Distortion of Data
63(1)
2.1 1 Research in Focus: Frequencies and Percents
64(1)
2.12 SPSS in Focus: Histograms, Bar Charts, and Pie Charts
65(1)
Chapter Summary
66(2)
Key Terms
68(1)
End-of-Chapter Problems
69(1)
Factual Problems
69(1)
Concept and Application Problems
69(4)
Problems in Research
73(3)
Chapter 3 Summarizing Data: Central Tendency
76(30)
3.1 Introduction to Central Tendency
77(1)
3.2 Measures of Central Tendency
78(8)
The Mean
78(2)
The Weighted Mean
80(2)
Making Sense: Making the Grade
81(1)
The Median
82(3)
The Mode
85(1)
3.3 Characteristics of the Mean
86(6)
Changing an Existing Score
86(1)
Adding a New Score or Removing an Existing Score
87(1)
Adding, Subtracting, Multiplying, or Dividing Each Score by a Constant
88(2)
Summing the Differences of Scores From Their Mean
90(1)
Summing the Squared Differences of Scores From Their Mean
90(2)
3.4 Choosing an Appropriate Measure of Central Tendency
92(5)
Using the Mean to Describe Data
92(1)
Using the Median to Describe Data
93(1)
Using the Mode to Describe Data
94(3)
3.5 Research in Focus: Describing Central Tendency
97(1)
3.6 SPSS in Focus: Mean, Median, and Mode
98(2)
Chapter Summary
100(1)
Key Terms
101(1)
End-of-Chapter Problems
101(1)
Factual Problems
101(1)
Concept and Application Problems
102(2)
Problems in Research
104(2)
Chapter 4 Summarizing Data: Variability
106(31)
4.1 Measuring Variability
107(1)
4.2 The Range
108(1)
4.3 Research in Focus: Reporting the Range
108(1)
4.4 Quartiles and lnterquartiles
109(2)
4.5 The Variance
111(4)
Population Variance
112(1)
Sample Variance
113(2)
4.6 Explaining Variance for Populations and Samples
115(4)
The Numerator: Why Square Deviations From the Mean?
115(1)
The Denominator: Sample Variance as an Unbiased Estimator
116(2)
The Denominator: Degrees of Freedom
118(1)
4.7 The Computational Formula for Variance
119(4)
4.8 The Standard Deviation
123(1)
4.9 What Does the Standard Deviation Tell Us?
124(2)
Making Sense: Standard Deviation and Nonnormal Distributions
126(1)
4.10 Characteristics of the Standard Deviation
126(3)
4.11 SPSS in Focus: Range, Variance, and Standard Deviation
129(1)
Chapter Summary
130(2)
Key Terms
132(1)
End-of-Chapter Problems
132(1)
Factual Problems
132(1)
Concept and Application Problems
132(2)
Problems in Research
134(3)
Part II. Probability And The Foundations Of Inferential Statistics 137(102)
Chapter 5 Probability
138(36)
5.1 Introduction to Probability
139(1)
5.2 Calculating Probability
139(3)
5.3 Probability and Relative Frequency
142(3)
5.4 The Relationship Between Multiple Outcomes
145(5)
Mutually Exclusive Outcomes
145(2)
Independent Outcomes
147(1)
Complementary Outcomes
148(1)
Conditional Outcomes
149(1)
5.5 Conditional Probabilities and Bayes's Theorem
150(2)
5.6 SPSS in Focus: Probability Tables
152(3)
Construct a Probability Table
152(1)
Construct a Conditional Probability Table
153(2)
5.7 Probability Distributions
155(2)
5.8 The Mean of a Probability Distribution and Expected Value
157(3)
Making Sense: Expected Value and the "Long-Term Mean"
159(1)
5.9 Research in Focus: When Are Risks Worth Taking?
160(1)
5.10 The Variance and Standard Deviation of a Probability Distribution
161(3)
5.11 Expected Value and the Binomial Distribution
164(2)
The Mean of a Binomial Distribution
165(1)
The Variance and Standard Deviation of a Binomial Distribution
165(1)
5.12 A Final Thought on the Likelihood of Random Behavioral Outcomes
166(1)
Chapter Summary
167(2)
Key Terms
169(1)
End-of-Chapter Problems
169(1)
Factual Problems
169(1)
Concept and Application Problems
170(2)
Problems in Research
172(2)
Chapter 6 Probability, Normal Distributions, and z Scores
174(34)
6.1 The Normal Distribution in Behavioral Science
175(1)
6.2 Characteristics of the Normal Distribution
175(3)
6.3 Research in Focus: The Statistical Norm
178(1)
6.4 The Standard Normal Distribution
179(2)
6.5 The Unit Normal Table: A Brief Introduction
181(2)
6.6 Locating Proportions
183(7)
Locating Proportions Above the Mean
184(2)
Locating Proportions Below the Mean
186(2)
Locating Proportions Between Two Values
188(2)
6.7 Locating Scores
190(3)
6.8 SPSS in Focus: Converting Raw Scores to Standard z Scores
193(4)
Making Sense: Standard Deviation and the Normal Distribution
195(2)
6.9 Going From Binomial to Normal
197(3)
6.10 The Normal Approximation to the Binomial Distribution
200(2)
Chapter Summary
202(2)
Key Terms
204(1)
End-of-Chapter Problems
204(1)
Factual Problems
204(1)
Concept and Application Problems
204(2)
Problems in Research
206(2)
Chapter 7 Probability and Sampling Distributions
208(31)
7.1 Selecting Samples From Populations
209(3)
Inferential Statistics and Sampling Distributions
209(1)
Sampling and Conditional Probabilities
210(2)
7.2 Selecting a Sample: Who's In and Who's Out?
212(4)
Sampling Strategy: The Basis for Statistical Theory
213(1)
Sampling Strategy: Most Used in Behavioral Research
214(2)
7.3 Sampling Distributions: The Mean
216(4)
Unbiased Estimator
216(1)
Central Limit Theorem
217(2)
Minimum Variance
219(1)
Overview of the Sample Mean
219(1)
7.4 Sampling Distributions: The Variance
220(4)
Unbiased Estimator
221(1)
Skewed Distribution Rule
222(1)
No Minimum Variance
222(2)
Making Sense: Minimum Variance Versus Unbiased Estimator
223(1)
Overview of the Sample Variance
224(1)
7.5 The Standard Error of the Mean
224(2)
7.6 Factors That Decrease Standard Error
226(1)
7.7 SPSS in Focus: Estimating the Standard Error of the Mean
227(2)
7.8 APA in Focus: Reporting the Standard Error
229(3)
7.9 Standard Normal Transformations With Sampling Distributions
232(2)
Chapter Summary
234(1)
Key Terms
235(1)
End-of-Chapter Problems
236(1)
Factual Problems
236(1)
Concept and Application Problems
236(1)
Problems in Research
237(2)
Part III. Making Inferences About One Or Two Means 239(124)
Chapter 8 Hypothesis Testing: Significance, Effect Size, and Power
240(34)
8.1 Inferential Statistics and Hypothesis Testing
241(2)
8.2 Four Steps to Hypothesis Testing
243(4)
Making Sense: Testing the Null Hypothesis
244(3)
8.3 Hypothesis Testing and Sampling Distributions
247(2)
8.4 Making a Decision: Types of Error
249(1)
Decision: Retain the Null Hypothesis
249(1)
Decision: Reject the Null Hypothesis
250(1)
8.5 Testing for Significance: Examples Using the z Test
250(7)
Nondirectional Tests (H1:not equal to)
251(3)
Directional Tests (H1: >or H1:<)
254(3)
8.6 Research in Focus: Directional Versus Nondirectional Tests
257(1)
8.7 Measuring the Size of an Effect: Cohen's d
258(3)
8.8 Effect Size, Power, and Sample Size
261(4)
The Relationship Between Effect Size and Power
261(3)
The Relationship Between Sample Size and Power
264(1)
8.9 Additional Factors That Increase Power
265(2)
Increasing Power: Increase Effect Size, Sample Size, and Alpha
265(1)
Increasing Power: Decrease Beta, Standard Deviation (sigma), and Standard Error
266(1)
8.10 SPSS in Focus: A Preview for
Chapters 9 to 18
267(1)
8.11 APA in Focus: Reporting the Test Statistic and Effect Size
267(1)
Chapter Summary
268(2)
Key Terms
270(1)
End-of-Chapter Problems
270(1)
Factual Problems
270(1)
Concept and Application Problems
270(2)
Problems in Research
272(2)
Chapter 9 Testing Means: One-Sample and Two-Independent-Sample t Tests
274(32)
9.1 Going From z to t
275(1)
9.2 The Degrees of Freedom
276(1)
9.3 Reading the tTable
277(2)
9.4 One-Sample tTest
279(4)
9.5 Effect Size for the One-Sample tTest
283(3)
Estimated Cohen's d
283(1)
Proportion of Variance
283(3)
9.6 SPSS in Focus: One-Sample tTest
286(2)
9.7 Two-Independent-Sample tTest
288(6)
Making Sense: The Pooled Sample Variance
292(2)
9.8 Effect Size for the Two-Independent- Sample tTest
294(3)
Estimated Cohen's d
295(1)
Proportion of Variance
295(2)
9.9 SPSS in Focus: Two-Independent-Sample tTest
297(2)
9.10 APA in Focus: Reporting the t Statistic and Effect Size
299(1)
Chapter Summary
299(2)
Key Terms
301(1)
End-of-Chapter Problems
302(1)
Factual Problems
302(1)
Concept and Application Problems
302(2)
Problems in Research
304(2)
Chapter 10 Testing Means: The Related-Samples t Test
306(57)
10.1 Related and Independent Samples
307(3)
The Repeated-Measures Design
307(1)
The Matched-Pairs Design
308(2)
10.2 Introduction to the Related-Samples tTest
310(3)
The Test Statistic
312(1)
Degrees of Freedom
312(1)
Assumptions
312(1)
10.3 The Related-Samples tTest: Repeated-Measures Design
313(4)
Making Sense: Increasing Power by Reducing Error
316(1)
10.4 SPSS in Focus: The Related-Samples tTest
317(2)
10.5 The Related-Samples tTest: Matched-Pairs Design
319(4)
10.6 Measuring Effect Size for the Related-Samples tTest
323(2)
Estimated Cohen's d
323(1)
Proportion of Variance
324(1)
10.7 Advantages for Selecting Related Samples
325(1)
10.8 APA in Focus: Reporting the t Statistic and Effect Size for Related Samples
326(1)
Chapter Summary
326(1)
Key Terms
327(1)
End-of-Chapter Problems
328(1)
Factual Problems
328(1)
Concept and Application Problems
328(3)
Problems in Research
331(27)
End-of-Chapter Problems
358(1)
Factual Problems
358(1)
Concept and Application Problems
359(2)
Problems in Research
361(2)
Part IV. Making Inferences About The Variability Of Two Or More Means 363(124)
Chapter 11 Estimation and Confidence Intervals
334(30)
11.1 Point Estimation and Interval Estimation
335(2)
11.2 The Process of Estimation
337(2)
11.3 Estimation for the One-Sample z Test
339(5)
Making Sense: Estimation, Significance, and Effect Size
343(1)
11.4 Estimation for the One-Sample tTest
344(3)
11.5 SPSS in Focus: Confidence Intervals for the One-Sample tTest
347(2)
11.6 Estimation for the Two-Independent-Sample tTest
349(1)
11.7 SPSS in Focus: Confidence Intervals for the Two-Independent-Sample tTest
350(1)
11.8 Estimation for the Related-Samples t Test
351(2)
11.9 SPSS in Focus: Confidence Intervals for the Related-Samples tTest
353(1)
11.10 Characteristics of Estimation: Precision and Certainty
354(2)
11.11 APA in Focus: Reporting Confidence Intervals
356(1)
Chapter Summary
357(1)
Key Terms
358(6)
Chapter 12 Analysis of Variance: One-Way Between- Subjects Design
364(40)
12.1 Analyzing Variance for Two or More Groups
365(1)
12.2 An Introduction to Analysis of Variance
366(4)
Identifying the Type of ANOVA
367(1)
Two Ways to Select Independent Samples
367(2)
Changes in Notation
369(1)
12.3 Sources of Variation and the Test Statistic
370(2)
12.4 Degrees of Freedom
372(3)
12.5 The One-Way Between-Subjects ANOVA
375(7)
Making Sense: Mean Squares and Variance
382(1)
12.6 What Is the Next Step?
382(1)
12.7 Post Hoc Comparisons
383(6)
Fisher's Least Significant Difference (LSD) Test
385(1)
Tukey's Honestly Significant Difference (HSD) Test
386(3)
12.8 SPSS in Focus: The One-Way Between-Subjects ANOVA
389(4)
12.9 Measuring Effect Size
393(2)
Eta-Squared
393(1)
Omega-Squared
394(1)
12.10 APA in Focus: Reporting the FStatistic, Significance, and Effect Size
395(1)
Chapter Summary
396(2)
Key Terms
398(1)
End-of-Chapter Problems
399(1)
Factual Problems
399(1)
Concept and Application Problems
399(3)
Problems in Research
402(2)
Chapter 13 Analysis of Variance: One-Way Within-Subjects (Repeated-Measures) Design
404(38)
13.1 Observing the Same Participants Across Groups
405(1)
The One-Way Within-Subjects ANOVA
405(1)
Selecting Related Samples: The Within-Subjects Design
406(1)
13.2 Sources of Variation and the Test Statistic
406(4)
Between-Groups Variation
407(1)
Error Variation
407(19)
Making Sense: Sources of Error
410(1)
13.3 Degrees of Freedom
410(1)
13.4 The One-Way Within-Subjects ANOVA
411(8)
Making Sense: Mean Squares and Variance
419(1)
13.5 Post Hoc Comparisons: Bonferroni Procedure
419(4)
13.6 SPSS in Focus: The One-Way Within-Subjects ANOVA
423(3)
13.7 Measuring Effect Size
426(2)
Partial Eta-Squared
426(1)
Partial Omega-Squared
427(1)
13.8 The Within-Subjects Design: Consistency and Power
428(5)
13.9 APA in Focus: Reporting the FStatistic, Significance, and Effect Size
433(1)
Chapter Summary
433(2)
Key Terms
435(1)
End-of-Chapter Problems
435(1)
Factual Problems
435(1)
Concept and Application Problems
436(3)
Problems in Research
439(3)
Chapter 14 Analysis of Variance: Two-Way Between-Subjects Factorial Design
442(45)
14.1 Observing Two Factors at the Same Time
443(1)
14.2 New Terminology and Notation
444(2)
14.3 Designs for the Two-Way ANOVA
446(3)
The 2-Between or Between-Subjects Design
446(1)
The 1-Between 1-Within or Mixed Design
447(1)
The 2-Within or Within-Subjects Design
448(1)
14.4 Describing Variability: Main Effects and Interactions
449(8)
Sources of Variability
449(3)
Testing Main Effects
452(1)
Testing the Interaction
453(3)
Making Sense: Graphing Interactions
455(1)
Outcomes and Order of Interpretation
456(1)
14.5 The Two-Way Between-Subjects ANOVA
457(9)
14.6 Analyzing Main Effects and Interactions
466(7)
Interactions: Simple Main Effect Tests
466(5)
Main Effects: Pairwise Comparisons
471(2)
14.7 Measuring Effect Size
473(1)
Eta-Squared
473(1)
Omega-Squared
473(1)
14.8 SPSS in Focus: The Two-Way Between-Subjects ANOVA
474(3)
14.9 APA in Focus: Reporting Main Effects, Interactions, and Effect Size
477(1)
Chapter Summary
478(2)
Key Terms
480(1)
End-of-Chapter Problems
480(1)
Factual Problems
480(1)
Concept and Application Problems
481(3)
Problems in Research
484(3)
Part V. Making Inferences About Patterns, Frequencies, And Ordinal Data 487
Chapter 15 Correlation
488(48)
15.1 The Structure of a Correlational Design
489(1)
15.2 Describing a Correlation
489(5)
The Direction of a Correlation
490(2)
The Strength of a Correlation
492(2)
15.3 Pearson Correlation Coefficient
494(7)
Making Sense: Understanding Covariance
496(3)
Effect Size: The Coefficient of Determination
499(1)
Hypothesis Testing: Testing for Significance
499(2)
15.4 SPSS in Focus: Pearson Correlation Coefficient
501(1)
15.5 Assumptions of Tests for Linear Correlations
502(3)
Homoscedasticity
502(1)
Linearity
502(1)
Normality
502(3)
15.6 Limitations in Interpretation: Causality, Outliers, and Restrictions of Range
505(4)
Causality
505(1)
Outliers
506(1)
Restriction of Range
507(2)
15.7 Alternative to Pearson r: Spearman Correlation Coefficient
509(3)
15.8 SPSS in Focus: Spearman Correlation Coefficient
512(1)
15.9 Alternative to Pearson r: Point-Biserial Correlation Coefficient
513(4)
15.10 SPSS in Focus: Point-Biserial Correlation Coefficient
517(2)
15.11 Alternative to Pearson r: Phi Correlation Coefficient
519(3)
15.12 SPSS in Focus: Phi Correlation Coefficient
522(2)
15.13 APA in Focus: Reporting Correlations
524(1)
Chapter Summary
524(3)
Key Terms
527(1)
End-of-Chapter Problems
527(1)
Factual Problems
527(1)
Concept and Application Problems
527(6)
Problems in Research
533(38)
Key Terms
571(1)
End-of-Chapter Problems
571(1)
Factual Problems
571(1)
Concept and Application Problems
572(3)
Problems in Research
575
Chapter 16 Linear Regression and Multiple Regression
536(42)
16.1 From Relationships to Predictions
537(1)
16.2 Fundamentals of Linear Regression
537(2)
16.3 What Makes the Regression Line the Best-Fitting Line?
539(2)
16.4 The Slope and y-Intercept of a Straight Line
541(2)
16.5 Using the Method of Least Squares to Find the Best Fit
543(4)
Making Sense: SP, SS, and the Slope of a Regression Line
545(2)
16.6 Using Analysis of Regression to Determine Significance
547(4)
16.7 SPSS in Focus: Analysis of Regression
551(2)
16.8 Using the Standard Error of Estimate to Measure Accuracy
553(4)
16.9 Introduction to Multiple Regression
557(1)
16.10 Computing and Evaluating Significance for Multiple Regression
558(4)
16.11 The beta Coefficient for Multiple Regression
562(1)
16.12 Evaluating Significance for the Relative Contribution of Each Predictor Variable
563(3)
Relative Contribution of x1
564(1)
Relative Contribution of x2
565(1)
16.13 SPSS in Focus: Multiple Regression Analysis
566(2)
16.14 APA in Focus: Reporting Regression Analysis
568(1)
Chapter Summary
569(9)
Chapter 17 Nonparametric Tests: Chi-Square Tests
578(34)
17.1 Tests for Nominal Data
579(1)
17.2 The Chi-Square Goodness-of-Fit Test
580(6)
The Test Statistic
582(1)
Making Sense: The Relative Size of a Discrepancy
582(1)
The Degrees of Freedom
583(3)
Making Sense: Degrees of Freedom
583(3)
Hypothesis Testing for Goodness of Fit
586(1)
17.3 SPSS in Focus: The Chi-Square Goodness-of-Fit Test
586(3)
17.4 Interpreting the Chi-Square Goodness-of-Fit Test
589(2)
Interpreting a Significant Chi-Square Goodness-of-Fit Test
589(1)
Using the Chi-Square Goodness-of- Fit Test to Support the Null Hypothesis
590(1)
17.5 Independent Observations and Expected Frequency Size
591(1)
17.6 The Chi-Square Test for Independence
592(6)
Determining Expected Frequencies
594(1)
The Test Statistic
595(1)
The Degrees of Freedom
596(1)
Hypothesis Testing for Independence
596(2)
17.7 The Relationship Between Chi-Square and the Phi Coefficient
598(2)
17.8 Measures of Effect Size
600(1)
Effect Size Using Proportion of Variance:Phi2= chi2/N
600(1)
Effect Size Using the Phi Coefficient: Phi2 = square root of chi2/N
600(1)
Effect Size Using Cramer's V: = square root of (chi2/(Nxdfsmaller))
601(1)
17.9 SPSS in Focus: The Chi-Square Test for Independence
601(3)
17.10 APA in Focus: Reporting the Chi-Square Test
604(1)
Chapter Summary
605(1)
Key Terms
606(1)
End-of-Chapter Problems
606(1)
Factual Problems
606(1)
Concept and Application Problems
607(2)
Problems in Research
609(3)
Chapter 18 Nonparametric Tests: Tests for Ordinal Data
612
18.1 Tests for Ordinal Data
613(2)
Scales of Measurement and Variance
613(1)
Making Sense: Reducing Variance
614(1)
Minimizing Bias: Tied Ranks
614(1)
18.2 The Sign Test
615(6)
The One-Sample Sign Test
615(2)
The Related-Samples Sign Test
617(3)
The Normal Approximation for the Sign Test
620(1)
18.3 SPSS in Focus: The Related-Samples Sign Test
621(2)
18.4 The Wilcoxon Signed-Ranks TTest
623(3)
Interpretation of the Test Statistic T
625(1)
The Normal Approximation for the Wilcoxon T
625(1)
18.5 SPSS in Focus: The Wilcoxon Signed-Ranks TTest
626(2)
18.6 The Mann-Whitney U Test
628(4)
Interpretation of the Test Statistic U
630(1)
Computing the Test Statistic U
631(1)
The Normal Approximation for U
631(1)
18.7 SPSS in Focus: The Mann-Whitney UTest
632(2)
18.8 The Kruskal-Wallis HTest
634(3)
Interpretation of the Test Statistic H
636(1)
18.9 SPSS in Focus: The Kruskal-Wallis H Test
637(2)
18.10 The Friedman Test
639(2)
Interpretation of the Test Statistic chi2R
641(1)
18.11 SPSS in Focus: The Friedman Test
641(2)
18.12 APA in Focus: Reporting Nonparametric Tests
643(1)
Chapter Summary
643(3)
Key Terms
646(1)
End-of-Chapter Problems
646(1)
Factual Problems
646(1)
Concept and Application Problems
646(3)
Problems in Research
649
Afterword: A Final Thought on the Role of Statistics in Research Methods AW-1
Appendix A. Basic Math Review and Summation Notation A-1
A.1 Positive and Negative Numbers
A-1
A.2 Addition
A-2
A.3 Subtraction
A-3
A.4 Multiplication
A-4
A.5 Division
A-5
A.6 Fractions
A-7
A.7 Decimals and Percents
A-9
A.8 Exponents and Roots
A-10
A.9 Order of Computation
A-11
A.10 Equations: Solving for x
A-13
A.11 Summation Notation
A-14
Key Terms
A-17
Review Problems
A-17
Appendix B. SPSS General Instructions Guide B-1
Appendix C. Statistical Tables C-1
C.1 The Unit Normal Table
C-1
C.2 Critical Values for the t Distribution
C-5
C.3 Critical Values for the F Distribution
C-7
C.4 The Studentized Range Statistic (q)
C-10
C.5 Critical Values for the Pearson Correlation
C-12
C.6 Critical Values for the Spearman Correlation
C-14
C.7 Critical Values of Chi-Square (chi2)
C-16
C.8 Distribution of Binomial Probabilities When p = .50
C-17
C.9 Wilcoxon Signed-Ranks TCritical Values
C-18
C.10A Critical Values of the Mann-Whitney U for alpha = .05
C-19
C.10B Critical Values of the Mann-Whitney U for alpha = .01
C-20
Appendix D.
Chapter Solutions for Even-Numbered Problems		 D-1
Glossary G-1
References R-1
Index I-1