Fundamental Statistics for the Behavioral Sciences

Cover
......Page 1
Title Page
......Page 7
Copyright
......Page 8
Brief Contents......Page 10
Contents......Page 11
Preface......Page 15
Ch 1: Introduction......Page 23
1.1: A Changing Field......Page 25
1.2: The Importance of Context......Page 26
1.3: Basic Terminology......Page 28
1.4: Selection among Statistical Procedures......Page 32
1.5: Using Computers......Page 34
1.6: Summary......Page 36
1.7: A Quick Review......Page 37
1.8: Exercises......Page 38
Ch 2: Basic Concepts......Page 40
2.1: Scales of Measurement......Page 41
2.2: Variables......Page 47
2.3: Random Sampling......Page 48
2.4: Notation......Page 50
2.5: Summary......Page 52
2.6: A Quick Review......Page 53
2.7: Exercises......Page 54
Ch 3: Displaying Data......Page 58
3.1: Plotting Data......Page 60
3.2: Stem-and-Leaf Displays......Page 63
3.3: Reading Graphs......Page 68
3.4: Alternative Methods of Plotting Data......Page 70
3.5: Describing Distributions......Page 73
3.6: Using Computer Programs to Display Data......Page 75
3.7: Summary......Page 76
3.8: A Quick Review......Page 77
3.9: Exercises......Page 78
Ch 4: Measures of Central Tendency......Page 84
4.2: The Median......Page 85
4.3: The Mean......Page 86
4.4: Relative Advantages and Disadvantages of the Mode, the Median, and the Mean......Page 87
4.5: Obtaining Measures of Central Tendency Using SPSS......Page 90
4.6: A Simple Demonstration - Seeing Statistics......Page 92
4.7: Summary......Page 95
4.9: Exercises......Page 96
Ch 5: Measures of Variability......Page 100
5.1: Range......Page 103
5.2: Interquartile Range and Other Range Statistics......Page 104
5.3: The Average Deviation......Page 105
5.4: The Variance......Page 106
5.5: The Standard Deviation......Page 108
5.6: Computational Formulae for the Variance and the Standard Deviation......Page 109
5.7: The Mean and the Variance as Estimators......Page 110
5.8: Boxplots: Graphical Representations of Dispersion and Extreme Scores......Page 112
5.9: A Return to Trimming......Page 116
5.10: Obtaining Measures of Dispersion Using SPSS......Page 118
5.11: The Moon Illusion......Page 119
5.12: Seeing Statistics......Page 122
5.13: Summary......Page 123
5.15: Exercises......Page 125
Ch 6: The Normal Distribution......Page 129
6.1: The Normal Distribution......Page 132
6.2: The Standard Normal Distribution......Page 136
6.3: Setting Probable Limits on an Observation......Page 142
6.4: Measures Related to z......Page 144
6.5: Seeing Statistics......Page 145
6.6: Summary......Page 146
6.8: Exercises......Page 147
Ch 7: Basic Concepts of Probability......Page 151
7.1: Probability......Page 152
7.2: Basic Terminology and Rules......Page 155
7.3: The Application of Probability to Controversial Issues......Page 160
7.4: Writing Up the Results......Page 163
7.5: Discrete versus Continuous Variables......Page 164
7.6: Probability Distributions for Discrete Variables......Page 165
7.7: Probability Distributions for Continuous Variables......Page 166
7.8: Summary......Page 168
7.10: Exercises......Page 170
Ch 8: Sampling Distributions and Hypothesis Testing......Page 173
8.1: Sampling Distributions and the Standard Error......Page 174
8.2: Two More Examples Involving Course Evaluations and Human Decision Making......Page 176
8.3: Hypothesis Testing......Page 179
8.4: The Null Hypothesis......Page 182
8.5: Test Statistics and Their Sampling Distributions......Page 184
8.6: Using the Normal Distribution to Test Hypotheses......Page 185
8.7: Type I and Type II Errors......Page 190
8.8: One- and Two-Tailed Tests......Page 194
8.9: Seeing Statistics......Page 198
8.10: A Final Example......Page 199
8.12: Summary......Page 201
8.13: A Quick Review......Page 202
8.14: Exercises......Page 203
Ch 9: Correlation......Page 206
9.1: Scatter Diagrams......Page 207
9.2: An Example: The Relationship between the Pace of Life and Heart Disease......Page 214
9.3: The Covariance......Page 215
9.4: The Pearson Product-Moment Correlation Coefficient (r)......Page 216
9.5: Correlations with Ranked Data......Page 218
9.6: Factors That Affect the Correlation......Page 220
9.7: Beware Extreme Observations......Page 223
9.8: Correlation and Causation......Page 225
9.9: If Something Looks Too Good to Be True, Perhaps It Is......Page 226
9.10: Testing the Significance of a Correlation Coefficient......Page 227
9.11: Intercorrelation Matrices......Page 230
9.12: Other Correlation Coefficients......Page 232
9.14: Seeing Statistics......Page 235
9.15: Does Rated Course Quality Relate to Expected Grade?......Page 238
9.16: Summary......Page 241
9.17: A Quick Review......Page 242
9.18: Exercises......Page 243
Ch 10: Regression......Page 247
10.1: The Relationship between Stress and Health......Page 249
10.3: The Regression Line......Page 251
10.4: The Accuracy of Prediction......Page 260
10.5: The Influence of Extreme Values......Page 265
10.6: Hypothesis Testing in Regression......Page 266
10.7: Computer Solution Using SPSS......Page 268
10.8: Seeing Statistics......Page 270
10.9: Course Ratings as a Function of Anticipated Grade......Page 275
10.10: Regression versus Correlation......Page 276
10.11: Summary......Page 277
10.12: A Quick Review......Page 278
10.13: Exercises......Page 279
Ch 11: Multiple Regression......Page 284
11.1: Overview......Page 286
11.2: Funding Our Schools......Page 289
11.3: Residuals......Page 300
11.4: Hypothesis Testing......Page 301
11.5: Refining the Regression Equation......Page 303
11.6: A Second Example: What Makes a Confident Mother?......Page 304
11.7: A Third Example: Psychological Symptoms in Cancer Patients......Page 307
11.8: Summary......Page 310
11.9: A Quick Review......Page 311
11.10: Exercises......Page 312
Ch 12: Hypothesis Tests Applied to Means: One Sample......Page 317
12.1: Sampling Distribution of the Mean......Page 319
12.2: Testing Hypotheses about Means When a is Known......Page 322
12.3: Testing a Sample Mean When a is Unknown......Page 326
12.5: A Second Example: The Moon Illusion......Page 332
12.6: How Large is Our Effect?......Page 333
12.7: Confidence Limits on the Mean......Page 334
12.8: Using SPSS to Run One-Sample t Tests......Page 338
12.9: A Good Guess is Better than Leaving It Blank......Page 339
12.10: Seeing Statistics......Page 342
12.11: Summary......Page 345
12.12: A Quick Review......Page 346
12.13: Exercises......Page 347
Ch 13: Hypothesis Tests Applied to Means: Two Related Samples......Page 349
13.1: Related Samples......Page 350
13.2: Student's t Applied to Difference Scores......Page 351
13.3: The Crowd within is Like the Crowd Without......Page 354
13.4: Advantages and Disadvantages of Using Related Samples......Page 356
13.5: How Large an Effect Have We Found?......Page 357
13.6: Confidence Limits on Changes......Page 359
13.8: Writing Up the Results......Page 360
13.9: Summary......Page 361
13.10: A Quick Review......Page 362
13.11: Exercises......Page 363
Ch 14: Hypothesis Tests Applied to Means: Two Independent Samples......Page 366
14.1: Distribution of Differences between Means......Page 367
14.2: Heterogeneity of Variance......Page 375
14.4: A Second Example with Two Independent Samples......Page 377
14.5: Effect Size Again......Page 379
14.6: Confidence Limits on u1 - u2......Page 380
14.7: Plotting the Results......Page 381
14.8: Writing Up the Results......Page 382
14.10: Do Lucky Charms Work?......Page 383
14.11: Seeing Statistics......Page 388
14.12: Summary......Page 389
14.13: A Quick Review......Page 390
14.14: Exercises......Page 391
Ch 15: Power......Page 394
15.1: The Basic Concept of Power......Page 397
15.2: Factors Affecting the Power of a Test......Page 399
15.3: Calculating Power the Traditional Way......Page 402
15.4: Power Calculations for the One-Sample t Test......Page 404
15.5: Power Calculations for Differences between Two Independent Means......Page 407
15.6: Power Calculations for the t Test for Related Samples......Page 410
15.7: Power Considerations in Terms of Sample Size......Page 411
15.8: You Don't Have to Do It by Hand......Page 412
15.9: Post-hoc (Retrospective) Power......Page 413
15.10: Summary......Page 414
15.12: Exercises......Page 415
Ch 16: One-Way Analysis of Variance......Page 418
16.1: The General Approach......Page 419
16.2: The Logic of the Analysis of Variance......Page 423
16.3: Calculations for the Analysis of Variance......Page 428
16.4: Unequal Sample Sizes......Page 435
16.5: Multiple Comparison Procedures......Page 437
16.7: The Size of the Effects......Page 446
16.8: Writing Up the Results......Page 449
16.9: The Use of SPSS for a One-Way Analysis of Variance......Page 450
16.10: A Final Worked Example......Page 451
16.11: Seeing Statistics......Page 454
16.12: Summary......Page 455
16.13: A Quick Review......Page 456
16.14: Exercises......Page 457
Ch 17: Factorial Analysis of Variance......Page 462
17.1: Factorial Designs......Page 463
17.2: The Eysenck Study......Page 466
17.3: Interactions......Page 471
17.4: Simple Effects......Page 473
17.5: Measures of Association and Effect Size......Page 475
17.6: Reporting the Results......Page 478
17.7: Unequal Sample Sizes......Page 479
17.8: Masculine Overcompensation Thesis: It's a Male Thing......Page 480
17.9: Using SPSS for Factorial Analysis of Variance......Page 483
17.10: Seeing Statistics......Page 484
17.11: Summary......Page 485
17.12: A Quick Review......Page 486
17.13: Exercises......Page 487
Ch 18: Repeated-Measures Analysis of Variance......Page 492
18.1: An Example: Depression as a Response to an Earthquake......Page 493
18.2: Multiple Comparisons......Page 496
18.3: Effect Size......Page 498
18.5: Advantages and Disadvantages of Repeated-Measures Designs......Page 499
18.6: Using SPSS to Analyze Data in a Repeated-Measures Design......Page 500
18.7: Writing Up the Results......Page 503
18.8: A Final Worked Example......Page 504
18.9: Summary......Page 506
18.11: Exercises......Page 507
Ch 19: Chi-Square......Page 510
19.1: One Classification Variable: The Chi-Square Goodness-of-Fit Test......Page 512
19.2: Two Classification Variables: Analysis of Contingency Tables......Page 518
19.3: Possible Improvements on Standard Chi-Square......Page 520
19.4: Chi-Square for Larger Contingency Tables......Page 522
19.5: The Problem of Small Expected Frequencies......Page 523
19.6: The Use of Chi-Square as a Test on Proportions......Page 524
19.7: SPSS Analysis of Contingency Tables......Page 526
19.8: Measures of Effect Size......Page 528
19.9: A Final Worked Example......Page 533
19.11: Seeing Statistics......Page 535
19.12: Summary......Page 536
19.13: A Quick Review......Page 537
19.14: Exercises......Page 538
Ch 20: Nonparametric and Distribution-Free Statistical Tests......Page 542
20.1: The Mann-Whitney Test......Page 546
20.2: Wilcoxon's Matched-Pairs Signed-Ranks Test......Page 553
20.3: Kruskal-Wallis One-Way Analysis of Variance......Page 558
20.4: Friedman's Rank Test for k Correlated Samples......Page 560
20.6: Writing Up the Results......Page 562
20.7: Summary......Page 563
20.8: A Quick Review......Page 564
20.9: Exercises......Page 565
Ch 21: Meta-Analysis......Page 569
Meta-Analysis......Page 570
21.1: A Brief Review of Effect Size Measures......Page 571
21.2: An Example - Child and Adolescent Depression......Page 575
21.3: A Second Example - Nicotine Gum and Smoking Cessation......Page 581
21.4: A Quick Review......Page 584
21.5: Exercises......Page 585
Appendix A: Arithmetic Review......Page 588
Addition and Subtraction......Page 589
Parentheses......Page 590
Fractions......Page 591
Algebraic Operations......Page 592
English Letter Symbols......Page 595
Tests on Sample Means......Page 598
Correlation and Regression......Page 599
Meta-Analysis......Page 601
Appendix D: Data Set......Page 602
Appendix E: Statistical Tables......Page 606
Table E.1: Upper Percentage Points of the x2 Distribution......Page 607
Table E.2: Significant Values of the Correlation Coefficient......Page 608
Table E.3: Critical Values of the F Distribution: Alpha = .05......Page 609
Table E.4: Critical Values of the F Distribution: Alpha = .01......Page 610
Table E.5: Power as a Function of d and Significance Level (a)......Page 611
Table E.6: Percentage Points of the t Distribution......Page 612
Table E.7: Critical Lower-Tail Values of T (and Their Associated Probabilities) for Wilcoxon's Matched-Pairs Signed-Ranks Test......Page 613
Table E.8: Critical Lower-Tail Values of Ws for the Mann-Whitney Test for Two Independent Samples (N1 < N2)......Page 614
Table E.9: Table of Uniform Random Numbers......Page 618
Table E.10: The Normal Distribution (z)......Page 620
Glossary......Page 624
References......Page 630
Answers to Exercises......Page 637
Index......Page 659