Statistics for the Behavior Sciences

by Gravetter, Frederick J.; Wallnau, Larry B.

• ISBN13: 9780534370886
• ISBN10: 0534370888
• Edition: Teacher
• Format: Hardcover
• Copyright: 1999-06-01
• Publisher: Cengage Learning

Table of Contents

Preface	p. xi
Introduction and Descriptive Statistics	p. 1
Introduction to Statistics	p. 3
Statistics, Science, and Observations	p. 5
Populations and Samples	p. 6
The Scientific Method and the Design of Research Studies	p. 12
Scales of Measurement	p. 22
Discrete and Continuous Variables	p. 25
Statistical Notation	p. 27
Summary	p. 32
Focus on Problem Solving	p. 33
Demonstrations 1.1 and 1.2	p. 33
Problems	p. 36
Frequency Distributions	p. 39
Overview	p. 41
Frequency Distribution Tables	p. 41
Frequency Distribution Graphs	p. 48
The Shape of a Frequency Distribution	p. 53
Percentiles, Percentile Ranks, and Interpolation	p. 55
Stem and Leaf Displays	p. 62
Summary	p. 65
Focus on Problem Solving	p. 66
Demonstrations 2.1 and 2.2	p. 67
Problems	p. 69
Central Tendency	p. 74
Overview	p. 75
The Mean	p. 77
The Median	p. 87
The Mode	p. 92
Selecting a Measure of Central Tendency	p. 95
Central Tendency and the Shape of the Distribution	p. 102
Summary	p. 104
Focus on Problem Solving	p. 105
Demonstrations 3.1 and 3.2	p. 106
Problems	p. 107
Variability	p. 111
Overview	p. 112
The Range	p. 113
The Interquartile Range and Semi-Interquartile Range	p. 115
Standard Deviation and Variance for a Population	p. 117
Standard Deviation and Variance for Samples	p. 125
Properties of the Standard Deviation	p. 132
Comparing Measures of Variability	p. 135
The Role of Variability in Descriptive and Inferential Statistics	p. 137
Summary	p. 140
Focus on Problem Solving	p. 141
Demonstration 4.1	p. 142
Problems	p. 143
Foundations of Inferential Statistics	p. 148
z-Scores: Location of Scores and Standardized Distributions	p. 150
Introduction to z-Scores	p. 151
z-Scores and Location in a Distribution	p. 153
Using z-Scores to Standardize a Distribution	p. 158
Other Standardized Distributions Based on z-Scores	p. 163
Summary	p. 166
Focus on Problem Solving	p. 167
Demonstrations 5.1 and 5.2	p. 167
Problems	p. 169
Probability	p. 172
Overview	p. 173
Introduction to Probability	p. 174
Probability and the Normal Distribution	p. 180
Percentiles and Percentile Ranks	p. 193
Probability and the Binomial Distribution	p. 198
Summary	p. 204
Focus on Problem Solving	p. 205
Demonstrations 6.1 and 6.2	p. 206
Problems	p. 209
Probability and Samples: the Distribution of Sample Means	p. 212
Overview	p. 213
The Distribution of Sample Means	p. 214
Probability and the Distribution of Sample Means	p. 220
More About Standard Error	p. 224
Summary	p. 231
Focus on Problem Solving	p. 232
Demonstration 7.1	p. 233
Problems	p. 234
Inferences About Means and Mean Differences	p. 238
Introduction to Hypothesis Testing	p. 242
The Logic of Hypothesis Testing	p. 243
Uncertainty and Errors in Hypothesis Testing	p. 253
An Example of a Hypothesis Test	p. 257
Directional (One-Tailed) Hypothesis Tests	p. 264
The General Elements of Hypothesis Testing: A Review	p. 269
Statistical Power	p. 271
Summary	p. 277
Focus on Problem Solving	p. 278
Demonstration 8.1	p. 279
Problems	p. 281
Introduction to the t Statistic	p. 285
Overview	p. 286
The t Statistic--A Substitute for z	p. 287
Hypothesis Tests with the t Statistic	p. 293
Summary	p. 304
Focus on Problem Solving	p. 304
Demonstration 9.1	p. 305
Problems	p. 307
Hypothesis Tests With Two Independent Samples	p. 310
Overview	p. 311
The t Statistic for an Independent-Measures Research Design	p. 313
Hypothesis Tests with the Independent-Measures t Statistic	p. 319
Assumptions Underlying the Independent-Measures t Formula	p. 328
Summary	p. 330
Focus on Problem Solving	p. 330
Demonstration 10.1	p. 331
Problems	p. 333
Hypothesis Tests With Related Samples	p. 338
Overview	p. 339
The t Statistic for Related Samples	p. 341
Hypothesis Tests for the Repeated-Measures Design	p. 345
Hypothesis Testing with a Matched-Subjects Design	p. 350
Uses and Assumptions for Related-Samples t Tests	p. 352
Summary	p. 356
Focus on Problem Solving	p. 356
Demonstration 11.1	p. 357
Problems	p. 359
Estimation	p. 365
An Overview of Estimation	p. 366
Estimation with the z-Score	p. 372
Estimation with the t Statistic	p. 378
Factors Affecting the Width of a Confidence Interval	p. 384
Summary	p. 387
Focus on Problem Solving	p. 388
Demonstrations 12.1 and 12.2	p. 388
Problems	p. 392
Introduction To Analysis of Variance	p. 395
Introduction	p. 397
The Logic of Analysis of Variance	p. 401
ANOVA Vocabulary, Notation, and Formulas	p. 405
The Distribution of F-Ratios	p. 413
Examples of Hypothesis Testing with ANOVA	p. 415
Post Hoc Tests	p. 425
The Relationship Between ANOVA and t Tests	p. 429
Summary	p. 431
Focus on Problem Solving	p. 433
Demonstration 13.1	p. 434
Problems	p. 437
Repeated-Measures Analysis of Variance (ANOVA)	p. 442
Overview	p. 443
Notation and Formulas for Repeated-Measures ANOVA	p. 449
Testing Hypothesis with the Repeated-Measures ANOVA	p. 458
Advantages of the Repeated-Measures Design	p. 462
Assumptions of the Repeated-Measures ANOVA	p. 464
Summary	p. 466
Focus on Problem Solving	p. 467
Demonstration 14.1	p. 468
Problems	p. 471
Two-Factor Analysis of Variance (Independent Measures)	p. 476
Overview	p. 478
Main Effects and Interactions	p. 479
Notation and Formulas	p. 488
Examples of the Two-Factor ANOVA	p. 495
Assumptions for the Two-Factor ANOVA	p. 507
Summary	p. 507
Focus on Problem Solving	p. 508
Demonstration 15.1	p. 509
Problems	p. 515
Correlations and Nonparametric Tests	p. 522
Correlation and Regression	p. 525
Overview	p. 526
The Pearson Correlation	p. 531
Understanding and Interpreting the Pearson Correlation	p. 536
Hypothesis Tests with the Pearson Correlation	p. 540
The Spearman Correlation	p. 545
Other Measures of Relationship	p. 552
Introduction to Regression	p. 556
Summary	p. 568
Focus on Problem Solving	p. 570
Demonstration 16.1 and 16.2	p. 571
Problems	p. 574
The Chi-Square Statistic: Tests for Goodness of Fit and Independence	p. 581
Parametric and Non-Parametric Statistical Tests	p. 582
The Chi-Square Test for Goodness of Fit	p. 583
The Chi-Square Test for Independence	p. 594
Assumptions and Restrictions for Chi-Square Tests	p. 604
Special Applications of the Chi-Square Tests	p. 605
Summary	p. 609
Focus on Problem Solving	p. 610
Demonstration 17.1	p. 611
Problems	p. 613
The Binomial Test	p. 619
Overview	p. 620
The Binomial Test	p. 623
The Relation Between Chi-Square and the Binomial Test	p. 626
The Sign Test	p. 627
Summary	p. 631
Focus on Problem Solving	p. 631
Demonstration 18.1	p. 632
Problems	p. 633
Statistical Techniques for Ordinal Data: Mann-Whitney, Wilcoxon, and Kruskal-Wallis Tests	p. 636
Data From An Ordinal Scale	p. 638
The Mann-Whitney U-Test	p. 640
The Wilcoxon Signed-Ranks Test	p. 648
The Kruskal-Wallis Test	p. 653
Summary	p. 656
Focus on Problem Solving	p. 657
Demonstrations 19.1, 19.2, and 19.3	p. 657
Problems	p. 661
Basic Mathematics Review	p. 667
Symbols and Notation	p. 669
Proportions: Fractions, Decimals, and Percentages	p. 671
Negative Numbers	p. 677
Basic Algebra: Solving Equations	p. 679
Exponents and Square Roots	p. 682
Statistical Tables	p. 690
Solutions for Odd-Numbered Problems in the Text	p. 705
Statistics Organizer	p. 727
References	p. 742
Index	p. 745
Table of Contents provided by Syndetics. All Rights Reserved.