Essentials of Statistics for the Behavioral Sciences

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  • Edition: 5th
  • Format: Paperback
  • Copyright: 2004-07-22
  • Publisher: Wadsworth Publishing
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Supplemental Materials

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  • The New copy of this book will include any supplemental materials advertised. Please check the title of the book to determine if it should include any access cards, study guides, lab manuals, CDs, etc.


This brief version of Gravetter and Wallnau's proven best-seller offers the straightforward instruction, accuracy, built-in learning aids, and wealth of real-world examples that professors AND students have come to appreciate. The authors take time to explain statistical procedures so that students can go beyond memorizing formulas and gain a conceptual understanding of statistics. By integrating applications to ensure that even students with a weak background in mathematics can understand statistics, the authors skillfully demonstrate that having an understanding of statistical procedures help them comprehend published findings, and become savvy consumers of information. Known for its exceptional accuracy and examples, this text also has a complete supplements package to support instructors with class preparation and testing.

Table of Contents

Introduction to Statisticsp. 1
Statistics, Science, and Observationsp. 2
Populations and Samplesp. 3
The Scientific Method and the Design of Research Studiesp. 8
Scales of Measurementp. 14
Discrete and Continuous Variablesp. 17
Statistical Notationp. 19
Summaryp. 24
Focus on Problem Solvingp. 25
Problemsp. 27
Frequency Distributionsp. 29
Introductionp. 30
Frequency Distribution Tablesp. 30
Frequency Distribution Graphsp. 36
The Shape of a Frequency Distributionp. 40
Summaryp. 43
Focus on Problem Solvingp. 44
Problemsp. 46
Central Tendencyp. 50
Introductionp. 51
The Meanp. 52
The Medianp. 60
The Modep. 62
Selecting a Measure of Central Tendencyp. 64
In the Literature: Reporting Measures of Central Tendencyp. 67
Central Tendency and the Shape of the Distributionp. 70
Summaryp. 72
Focus on Problem Solvingp. 73
Problemsp. 74
Variabilityp. 76
Introductionp. 77
The Rangep. 78
The Interquartile Range and Semi-interquartile Rangep. 79
Standard Deviation and Variance for a Populationp. 81
Standard Deviation and Variance for Samplesp. 88
More about Variance and Standard Deviationp. 92
In the Literature: Reporting the Standard Deviationp. 97
Summaryp. 98
Focus on Problem Solvingp. 99
Problemsp. 100
z-Scores: Location of Scores and Standardized Distributionsp. 103
Overviewp. 104
Introduction to z-Scoresp. 104
z-Scores and Location in a Distributionp. 106
Using z-Scores to Standardize a Distributionp. 110
Other Standardized Distributions Based on z-Scoresp. 113
Summaryp. 116
Focus on Problem Solvingp. 116
Problemsp. 119
Probabilityp. 121
Introduction to Probabilityp. 122
Probability and the Normal Distributionp. 127
Summaryp. 139
Focus on Problem Solvingp. 139
Problemsp. 141
Probability and Samples: The Distribution of Sample Meansp. 144
Samples and Sampling Errorp. 145
The Distribution of Sample Meansp. 145
Probability and the Distribution of Sample Meansp. 152
More about Standard Errorp. 155
In the Literature: Reporting Standard Errorp. 158
Summaryp. 161
Focus on Problem Solvingp. 161
Problemsp. 163
Introduction to Hypothesis Testingp. 166
The Logic of Hypothesis Testingp. 167
Uncertainty and Errors in Hypothesis Testingp. 176
An Example of a Hypothesis Testp. 180
In the Literature: Reporting the Results of the Statistical Testp. 182
Directional (One-Tailed) Hypothesis Testsp. 186
The General Elements of Hypothesis Testing: A Reviewp. 190
Summaryp. 193
Focus on Problem Solvingp. 194
Problemsp. 196
Introduction to the t Statisticp. 200
Overviewp. 201
Hypothesis Tests with the t Statisticp. 207
In the Literature: Reporting the Results of a t Testp. 211
Summaryp. 216
Focus on Problem Solvingp. 217
Problemsp. 219
The t Test for Two Independent Samplesp. 222
Overviewp. 223
The t Statistic for an Independent-Measures Research Designp. 224
Hypothesis Tests with the Independent-Measures t Statisticp. 230
In the Literature: Reporting the Results of an Independent-Measures t Testp. 234
Assumptions Underlying the Independent-Measures t Formulap. 239
Summaryp. 241
Focus on Problem Solvingp. 242
Problemsp. 244
The t Test for Two Related Samplesp. 249
Overviewp. 250
The t Statistic for Related Samplesp. 251
Hypothesis Tests for the Repeated-Measures Designp. 255
In the Literature: Reporting the Results of a Repeated-Measures t Testp. 258
Uses and Assumptions for Related-Samples t Testsp. 261
Summaryp. 264
Focus on Problem Solvingp. 265
Problemsp. 268
Estimationp. 272
An Overview of Estimationp. 273
Estimation with the t Statisticp. 278
A Final Look at Estimationp. 287
Summaryp. 289
Focus on Problem Solvingp. 290
Problemsp. 294
Introduction to Analysis of Variancep. 298
Introductionp. 299
The Logic of Analysis of Variancep. 302
ANOVA Notation and Formulasp. 306
The Distribution of F-Ratiosp. 314
Examples of Hypothesis Testing with ANOVAp. 316
In the Literature: Reporting the Results of Analysis of Variancep. 319
Post Hoc Testsp. 327
Summaryp. 333
Focus on Problem Solvingp. 333
Problemsp. 336
More Advanced Analysis of Variance: Repeated-Measures and Two-Factor Designsp. 341
Overviewp. 342
Repeated-Measures Analysis of Variance (ANOVA)p. 342
In the Literature: Reporting the Results of a Repeated-Measure ANOVAp. 353
Two-Factor Analysis of Variance (Independent Measures)p. 355
In the Literature: Reporting the Results of a Two-Factor ANOVAp. 369
Summaryp. 373
Focus on Problem Solvingp. 373
Problemsp. 379
Correlation and Regressionp. 384
Introductionp. 385
The Pearson Correlationp. 388
Using and Interpreting the Pearson Correlationp. 393
Hypothesis Tests with the Pearson Correlationp. 399
In the Literature: Reporting Correlationsp. 401
The Spearman Correlationp. 404
Introduction to Regressionp. 410
Summaryp. 417
Focus on Problem Solvingp. 418
Problemsp. 421
The Chi-Square Statistic: Tests for Goodness of Fit and Independencep. 426
Parametric and Nonparametric Statistical Testsp. 427
The Chi-Square Test for Goodness of Fitp. 428
In the Literature: Reporting the Results for Chi-Squarep. 436
The Chi-Square Test for Independencep. 438
Assumptions and Restrictions for Chi-Square Testsp. 448
Summaryp. 449
Focus on Problem Solvingp. 450
Problemsp. 453
Basic Mathematics Reviewp. 1
Statistical Tablesp. 24
Solutions for Odd-Numbered Problems in the Textp. 35
Statistics Organizerp. 50
Referencesp. 61
Indexp. 62
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