Essentials of Statistics for the Behavioral Sciences

by Gravetter, Frederick J; Wallnau, Larry B.

• ISBN13: 9780534633967
• ISBN10: 053463396X
• Additional ISBN(s): 9780495383949, 9780534586171
• Edition: 5th
• Format: Paperback
• Copyright: 2004-07-22
• Publisher: Wadsworth Publishing
• More Book Details
• Purchase Benefits

Summary

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 Statistics	p. 1
Statistics, Science, and Observations	p. 2
Populations and Samples	p. 3
The Scientific Method and the Design of Research Studies	p. 8
Scales of Measurement	p. 14
Discrete and Continuous Variables	p. 17
Statistical Notation	p. 19
Summary	p. 24
Focus on Problem Solving	p. 25
Problems	p. 27
Frequency Distributions	p. 29
Introduction	p. 30
Frequency Distribution Tables	p. 30
Frequency Distribution Graphs	p. 36
The Shape of a Frequency Distribution	p. 40
Summary	p. 43
Focus on Problem Solving	p. 44
Problems	p. 46
Central Tendency	p. 50
Introduction	p. 51
The Mean	p. 52
The Median	p. 60
The Mode	p. 62
Selecting a Measure of Central Tendency	p. 64
In the Literature: Reporting Measures of Central Tendency	p. 67
Central Tendency and the Shape of the Distribution	p. 70
Summary	p. 72
Focus on Problem Solving	p. 73
Problems	p. 74
Variability	p. 76
Introduction	p. 77
The Range	p. 78
The Interquartile Range and Semi-interquartile Range	p. 79
Standard Deviation and Variance for a Population	p. 81
Standard Deviation and Variance for Samples	p. 88
More about Variance and Standard Deviation	p. 92
In the Literature: Reporting the Standard Deviation	p. 97
Summary	p. 98
Focus on Problem Solving	p. 99
Problems	p. 100
z-Scores: Location of Scores and Standardized Distributions	p. 103
Overview	p. 104
Introduction to z-Scores	p. 104
z-Scores and Location in a Distribution	p. 106
Using z-Scores to Standardize a Distribution	p. 110
Other Standardized Distributions Based on z-Scores	p. 113
Summary	p. 116
Focus on Problem Solving	p. 116
Problems	p. 119
Probability	p. 121
Introduction to Probability	p. 122
Probability and the Normal Distribution	p. 127
Summary	p. 139
Focus on Problem Solving	p. 139
Problems	p. 141
Probability and Samples: The Distribution of Sample Means	p. 144
Samples and Sampling Error	p. 145
The Distribution of Sample Means	p. 145
Probability and the Distribution of Sample Means	p. 152
More about Standard Error	p. 155
In the Literature: Reporting Standard Error	p. 158
Summary	p. 161
Focus on Problem Solving	p. 161
Problems	p. 163
Introduction to Hypothesis Testing	p. 166
The Logic of Hypothesis Testing	p. 167
Uncertainty and Errors in Hypothesis Testing	p. 176
An Example of a Hypothesis Test	p. 180
In the Literature: Reporting the Results of the Statistical Test	p. 182
Directional (One-Tailed) Hypothesis Tests	p. 186
The General Elements of Hypothesis Testing: A Review	p. 190
Summary	p. 193
Focus on Problem Solving	p. 194
Problems	p. 196
Introduction to the t Statistic	p. 200
Overview	p. 201
Hypothesis Tests with the t Statistic	p. 207
In the Literature: Reporting the Results of a t Test	p. 211
Summary	p. 216
Focus on Problem Solving	p. 217
Problems	p. 219
The t Test for Two Independent Samples	p. 222
Overview	p. 223
The t Statistic for an Independent-Measures Research Design	p. 224
Hypothesis Tests with the Independent-Measures t Statistic	p. 230
In the Literature: Reporting the Results of an Independent-Measures t Test	p. 234
Assumptions Underlying the Independent-Measures t Formula	p. 239
Summary	p. 241
Focus on Problem Solving	p. 242
Problems	p. 244
The t Test for Two Related Samples	p. 249
Overview	p. 250
The t Statistic for Related Samples	p. 251
Hypothesis Tests for the Repeated-Measures Design	p. 255
In the Literature: Reporting the Results of a Repeated-Measures t Test	p. 258
Uses and Assumptions for Related-Samples t Tests	p. 261
Summary	p. 264
Focus on Problem Solving	p. 265
Problems	p. 268
Estimation	p. 272
An Overview of Estimation	p. 273
Estimation with the t Statistic	p. 278
A Final Look at Estimation	p. 287
Summary	p. 289
Focus on Problem Solving	p. 290
Problems	p. 294
Introduction to Analysis of Variance	p. 298
Introduction	p. 299
The Logic of Analysis of Variance	p. 302
ANOVA Notation and Formulas	p. 306
The Distribution of F-Ratios	p. 314
Examples of Hypothesis Testing with ANOVA	p. 316
In the Literature: Reporting the Results of Analysis of Variance	p. 319
Post Hoc Tests	p. 327
Summary	p. 333
Focus on Problem Solving	p. 333
Problems	p. 336
More Advanced Analysis of Variance: Repeated-Measures and Two-Factor Designs	p. 341
Overview	p. 342
Repeated-Measures Analysis of Variance (ANOVA)	p. 342
In the Literature: Reporting the Results of a Repeated-Measure ANOVA	p. 353
Two-Factor Analysis of Variance (Independent Measures)	p. 355
In the Literature: Reporting the Results of a Two-Factor ANOVA	p. 369
Summary	p. 373
Focus on Problem Solving	p. 373
Problems	p. 379
Correlation and Regression	p. 384
Introduction	p. 385
The Pearson Correlation	p. 388
Using and Interpreting the Pearson Correlation	p. 393
Hypothesis Tests with the Pearson Correlation	p. 399
In the Literature: Reporting Correlations	p. 401
The Spearman Correlation	p. 404
Introduction to Regression	p. 410
Summary	p. 417
Focus on Problem Solving	p. 418
Problems	p. 421
The Chi-Square Statistic: Tests for Goodness of Fit and Independence	p. 426
Parametric and Nonparametric Statistical Tests	p. 427
The Chi-Square Test for Goodness of Fit	p. 428
In the Literature: Reporting the Results for Chi-Square	p. 436
The Chi-Square Test for Independence	p. 438
Assumptions and Restrictions for Chi-Square Tests	p. 448
Summary	p. 449
Focus on Problem Solving	p. 450
Problems	p. 453
Basic Mathematics Review	p. 1
Statistical Tables	p. 24
Solutions for Odd-Numbered Problems in the Text	p. 35
Statistics Organizer	p. 50
References	p. 61
Index	p. 62
Table of Contents provided by Syndetics. All Rights Reserved.