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Statistics for the Behavioral Sciences / Edition 4

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Overview

Now your students can become intelligent consumers of scientific research, without being overwhelmed by the statistics! Jaccard and Becker's text teaches students the basic skills for analyzing data and helps them become intelligent consumers of scientific information. Praised for its real-life applications, the text tells students when to use a particular statistic, why they should use it, and how the statistic should be computed and interpreted.Because many students, given a set of data, cannot determine where to begin in answering relevant research questions, the authors explicate the issues involved in selecting a statistical test. Each statistical technique is introduced by giving instances where the test is most typically applied followed by an interesting research example (each example is taken from psychology literature).
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Editorial Reviews

Booknews
An introductory undergraduate level text focusing as much on the intelligent use of scientific information as on basic skills for analyzing data. New to this edition are expanded sections on graphs and exploratory data analysis, a discussion of the use of computers, a new section on interaction comparisons, and new material on inferential aspects of prediction. Annotation c. by Book News, Inc., Portland, Or.
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Product Details

  • ISBN-13: 9780534569259
  • Publisher: Cengage Learning
  • Publication date: 10/29/2001
  • Edition description: REV
  • Edition number: 4
  • Pages: 688
  • Product dimensions: 7.32 (w) x 9.50 (h) x 1.20 (d)

Table of Contents

Preface xv
To the Student xxi
Part 1 Statistical Preliminaries 1
Chapter 1 Introduction and Mathematical Preliminaries 2
1.1 The Study of Statistics 2
1.2 Research in the Behavioral Sciences 4
1.3 Variables 5
1.4 Measurement 6
1.5 Discrete and Continuous Variables 14
1.6 Populations and Samples 16
Box 1.1 Biased Sampling 17
1.7 Descriptive and Inferential Statistics 18
1.8 The Concept of Probability 19
1.9 Mathematical Preliminaries: A Review 20
1.10 Statistics and Computers 28
Summary 29
Chapter 2 Frequency and Probability Distributions 34
2.1 Frequency Distributions for Quantitative Variables: Ungrouped Scores 34
2.2 Frequency Distributions for Quantitative Variables: Grouped Scores 38
2.3 Frequency Distributions for Qualitative Variables 41
2.4 Outliers 42
2.5 Frequency Graphs 43
2.6 Misleading Graphs 51
2.7 Graphs of Relative Frequencies, Percentages, Cumulative Frequencies, and Cumulative Relative Frequencies 52
2.8 Probability Distributions 53
2.9 Empirical and Theoretical Distributions 56
2.10 Method of Presentation 57
2.11 Examples from the Literature 59
Summary 63
Chapter 3 Measures of Central Tendency and Variability 67
3.1 Measures of Central Tendency for Quantitative Variables 68
3.2 Measures of Variability for Quantitative Variables 78
3.3 Computational Formula for the Sum of Squares 83
3.4 Relationship Between Central Tendency and Variability 85
3.5 Graphs of Central Tendency and Variability 86
3.6 Measures of Central Tendency and Variability for Qualitative Variables 89
3.7 Skewness and Kurtosis 90
3.8 Sample Versus Population Notation 91
3.9 Method of Presentation 91
3.10 Example from the Literature 92
Summary 95
Chapter 4 Percentiles, Percentile Ranks, Standard Scores, and the Normal Distribution 100
4.1 Percentiles and Percentile Ranks 101
4.2 Standard Scores 105
4.3 Standard Scores and the Normal Distribution 109
4.4 Standard Scores and the Shape of the Distribution 113
4.5 Method of Presentation 113
Summary 120
Appendix 4.1 The Normal Distribution Formula 121
Chapter 5 Pearson Correlation and Regression: Descriptive Aspects 125
5.1 Use of Pearson Correlation 125
5.2 The Linear Model 126
5.3 The Pearson Correlation Coefficient 130
5.4 Correlation and Causation 138
5.5 Interpreting the Magnitude of a Correlation Coefficient 139
5.6 Regression 140
5.7 Additional Issues Associated with the Use of Correlation and Regression 145
Summary 153
Chapter 6 Probability 157
6.1 Probabilities of Simple Events 159
6.2 Conditional Probabilities 160
6.3 Joint Probabilities 161
6.4 Adding Probabilities 162
6.5 Relationships Among Probabilities 162
6.6 Sampling with Versus Without Replacement 164
Box 6.1 Beliefs and Probability Theory 165
6.7 Counting Rules 166
6.8 The Binomial Expression 169
Summary 176
Chapter 7 Estimation and Sampling Distributions 181
7.1 Finite Versus Infinite Populations 181
7.2 Estimation of the Population Mean 182
7.3 Estimation of the Population Variance and Standard Deviation 184
7.4 Degrees of Freedom 187
7.5 Sampling Distribution of the Mean and the Central Limit Theorem 188
Box 7.1 Polls and Random Samples 191
7.6 Types of Sampling Distributions 197
Summary 202
Chapter 8 Hypothesis Testing: Inferences About a Single Mean 205
8.1 A Simple Analogy for Principles of Hypothesis Testing 205
8.2 Statistical Inference and the Normal Distribution: The One-Sample z Test 206
8.3 Defining Expected and Unexpected Results 210
8.4 Failing to Reject Versus Accepting the Null Hypothesis 211
8.5 Type I and Type II Errors 212
8.6 Effects of Alpha and Sample Size on the Power of Statistical Tests 214
8.7 Statistical and Real-World Significance 216
8.8 Directional Versus Nondirectional Tests 216
8.9 Statistical Inference Using Estimated Standard Errors: The One-Sample t Test 219
8.10 Confidence Intervals 225
8.11 Method of Presentation 229
8.12 Examples from the Literature 231
Summary 233
Part 2 The Analysis of Bivariate Relationships 239
Chapter 9 Research Design and Statistical Preliminaries for Analyzing Bivariate Relationships 240
9.1 Principles of Research Design: Statistical Implications 240
Box 9.1 Confounding and Disturbance Variables 247
9.2 Selecting the Appropriate Statistical Test to Analyze a Relationship: A Preview 251
Summary 255
Chapter 10 Independent Groups t Test 259
10.1 Use of the Independent Groups t Test 259
10.2 Inference of a Relationship Using the Independent Groups t Test 261
10.3 Strength of the Relationship 271
10.4 Nature of the Relationship 280
10.5 Methodological Considerations 281
10.6 Numerical Example 281
10.7 Planning an Investigation Using the Independent Groups t Test 284
10.8 Method of Presentation 286
10.9 Examples from the Literature 287
Summary 294
Chapter 11 Correlated Groups t Test 302
11.1 Use of the Correlated Groups t Test 302
11.2 Inference of a Relationship Using the Correlated Groups t Test 303
11.3 Strength of the Relationship 308
11.4 Nature of the Relationship 311
11.5 Methodological Considerations 311
11.6 Power of Correlated Groups Versus Independent Groups t Tests 312
11.7 Numerical Example 314
11.8 Planning an Investigation Using the Correlated Groups t Test 316
11.9 Method of Presentation 317
11.10 Examples from the Literature 318
Summary 321
Appendix 11.1 Computational Procedures for the Nullified Score Approach 322
Chapter 12 One-Way Between-Subjects Analysis of Variance 329
12.1 Use of One-Way Between-Subjects Analysis of Variance 329
12.2 Inference of a Relationship Using One-Way Between-Subjects Analysis of Variance 330
12.3 Relationship of the F Test to the t Test 344
12.4 Strength of the Relationship 344
12.5 Nature of the Relationship 345
12.6 Unstandardized Effect Sizes and Confidence Intervals 349
12.7 Methodological Considerations 350
12.8 Numerical Example 350
12.9 Planning an Investigation Using One-Way Between-Subjects Analysis of Variance 354
12.10 Method of Presentation 354
12.11 Examples from the Literature 356
Summary 360
Appendix 12.1 Rationale for the Degrees of Freedom 361
Chapter 13 One-Way Repeated Measures Analysis of Variance 369
13.1 Use of One-Way Repeated Measures Analysis of Variance 369
13.2 Inference of a Relationship Using One-Way Repeated Measures Analysis of Variance 371
13.3 Strength of the Relationship 380
13.4 Nature of the Relationship 381
13.5 Unstandardized Effect Size and Confidence Intervals 383
13.6 Methodological Considerations 383
13.7 Numerical Example 385
13.8 Planning an Investigation Using One-Way Repeated Measures Analysis of Variance 388
13.9 Method of Presentation 389
13.10 Examples from the Literature 390
Summary 395
Appendix 13.1 Determining the Nature of the Relationship Under Sphericity Violations 395
Chapter 14 Pearson Correlation and Regression: Inferential Aspects 402
14.1 Use of Pearson Correlation 402
14.2 Inference of a Relationship Using Pearson Correlation 403
14.3 Strength of the Relationship 407
14.4 Confidence Intervals for the Correlation Coefficient 407
14.5 Nature of the Relationship 408
14.6 Planning an Investigation Using Pearson Correlation 408
14.7 Method of Presentation for Pearson Correlation 408
14.8 Examples from the Literature 409
14.9 Regression 411
14.10 Numerical Example 414
14.11 Method of Presentation for Regression 418
Summary 423
Appendix 14.1 Testing Null Hypotheses Other Than [rho] = 0 423
Appendix 14.2 Confidence Intervals for the Correlation Coefficient 425
Chapter 15 Chi-Square Test 433
15.1 Use of the Chi-Square Test 433
15.2 Two-Way Contingency Tables 434
15.3 Chi-Square Tests of Independence and Homogeneity 435
15.4 Inference of a Relationship Using the Chi-Square Test 435
15.5 2 x 2 Tables 441
15.6 Strength of the Relationship 442
15.7 Nature of the Relationship 443
15.8 Methodological Considerations 444
15.9 Numerical Example 445
15.10 Use of Quantitative Variables in the Chi-Square Test 446
15.11 Planning an Investigation Using the Chi-Square Test 447
15.12 Method of Presentation 448
15.13 Examples from the Literature 449
15.14 Chi-Square Goodness-of-Fit Test 451
Summary 455
Appendix 15.1 Determining the Nature of the Relationship Using a Modified Bonferroni Procedure 456
Chapter 16 Nonparametric Statistics 463
16.1 Rank Scores 464
16.2 Nonparametric Statistics and Outliers 466
16.3 Analysis of Ranked Data Using Parametric Formulas 467
16.4 Rank Tests for Two Independent Groups 467
16.5 Rank Test for Two Correlated Groups 471
16.6 Rank Test for Three or More Independent Groups 474
16.7 Rank Test for Three or More Correlated Groups 477
16.8 Rank Test for Correlation 480
16.9 Examples from the Literature 483
Summary 486
Appendix 16.1 Corrections for Ties for Nonparametric Rank Tests 486
Part 3 Additional Topics 495
Chapter 17 Two-Way Between-Subjects Analysis of Variance 496
17.1 Factorial Designs 497
17.2 Use of Two-Way Between-Subjects Analysis of Variance 498
17.3 The Concepts of Main Effects and Interactions 499
17.4 Inference of Relationships Using Two-Way Between-Subjects Analysis of Variance 506
17.5 Strength of the Relationships 514
17.6 Nature of the Relationships 515
17.7 Methodological Considerations 518
17.8 Numerical Example 518
17.9 Unequal Sample Sizes 526
17.10 Planning an Investigation Using Two-Way Between-Subjects Analysis of Variance 527
17.11 Method of Presentation 529
17.12 Examples from the Literature 531
Summary 536
Chapter 18 Overview and Extension: Selecting the Appropriate Statistical Test for Analyzing Bivariate Relationships and Procedures for More Complex Designs 544
18.1 Selecting the Appropriate Statistical Test for Analyzing Bivariate Relationships 544
18.2 Case I: The Relationship Between Two Qualitative Variables 545
18.3 Case II: The Relationship Between a Qualitative Independent Variable and a Quantitative Dependent Variable 545
18.4 Case III: The Relationship Between a Quantitative Independent Variable and a Qualitative Dependent Variable 549
18.5 Case IV: The Relationship Between Two Quantitative Variables 549
18.6 Procedures for More Complex Designs 550
18.7 Alternative Approaches to Null Hypothesis Testing 553
Summary 554
Appendix A Table of Random Numbers 559
Appendix B Proportions of Scores in a Normal Distribution 562
Appendix C Factorials 572
Appendix D Critical Values for the t Distribution 573
Appendix E Power and Sample Size 575
Appendix F Critical Values for the F Distribution 599
Appendix G Studentized Range Values (q) 603
Appendix H Critical Values for Pearson r 606
Appendix I Fisher's Transformation of Pearson r(r') 608
Appendix J Critical Values for the Chi-Square Distribution 610
Appendix K Critical Values for the Mann-Whitney U Test 612
Appendix L Critical Values for the Wilcoxon Signed-Rank Test 615
Appendix M Critical Values for Spearman r 617
Appendix N Formulas for Unbiased Estimators of Proportion of Explained Variance 619
Answers to Selected Exercises 620
Glossary of Major Symbols 639
References 644
Index 651
Credits 658
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