Essentials of Statistics for the Behavioral Sciences

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Does the thought of taking a statistics course make your students nervous? Authors Frederick Gravetter and Larry B. Wallnau use interesting real-world examples and applications to quell student fears and to reveal the ESSENTIALS OF STATISTICS FOR THE BEHAVIORAL SCIENCES. This book helps students get beyond thinking of statistics as merely a course they have to take and come to appreciate it as a set of essential tools that helps us make sense of data in our information-driven world. Gravetter and Wallnau ...
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Overview

Does the thought of taking a statistics course make your students nervous? Authors Frederick Gravetter and Larry B. Wallnau use interesting real-world examples and applications to quell student fears and to reveal the ESSENTIALS OF STATISTICS FOR THE BEHAVIORAL SCIENCES. This book helps students get beyond thinking of statistics as merely a course they have to take and come to appreciate it as a set of essential tools that helps us make sense of data in our information-driven world. Gravetter and Wallnau skillfully demonstrate that having a basic understanding of a variety of statistical procedures will help students understand published findings, as well as become savvy consumers of information. The authors employ an intuitive, straightforward writing style as well as numerous learning checks, both of which support students' interest in and understanding of the material.

Covers frequency distributions/central tendency/ probability/hypothesis tests w/2 independent samples/etc.

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Editorial Reviews

Booknews
Teaches methods of statistics and how to apply them appropriately. This fifth edition contains revised problems and learning checks, and is divided into sections on descriptive statistics, foundations of inferential statistics, inferential statistics for sample mean differences, and non-parametric statistics. Each section is preceded by a brief synopsis of goals and direction of material to be covered. Includes chapter summaries, problem solving tips, worked examples, and problems. The authors are affiliated with the State University of New York College at Brockport. Annotation c. Book News, Inc., Portland, OR (booknews.com)
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Product Details

  • ISBN-13: 9780314772916
  • Publisher: West Group
  • Publication date: 10/28/1991
  • Pages: 405

Table of Contents

Chapter 1 Introduction to Statistics 1
1.1 Statistics, Science, and Observations 2
1.2 Populations and Samples 3
1.3 The Scientific Method and the Design of Research Studies 8
1.4 Scales of Measurement 14
1.5 Discrete and Continuous Variables 17
1.6 Statistical Notation 19
Summary 24
Focus on Problem Solving 25
Problems 27
Chapter 2 Frequency Distributions 29
2.1 Introduction 30
2.2 Frequency Distribution Tables 30
2.3 Frequency Distribution Graphs 36
2.4 The Shape of a Frequency Distribution 40
Summary 43
Focus on Problem Solving 44
Problems 46
Chapter 3 Central Tendency 50
3.1 Introduction 51
3.2 The Mean 52
3.3 The Median 60
3.4 The Mode 62
3.5 Selecting a Measure of Central Tendency 64
In the Literature: Reporting Measures of Central Tendency 67
3.6 Central Tendency and the Shape of the Distribution 70
Summary 72
Focus on Problem Solving 73
Problems 74
Chapter 4 Variability 76
4.1 Introduction 77
4.2 The Range 78
4.3 The Interquartile Range and Semi-interquartile Range 79
4.4 Standard Deviation and Variance for a Population 81
4.5 Standard Deviation and Variance for Samples 88
4.6 More about Variance and Standard Deviation 92
In the Literature: Reporting the Standard Deviation 97
Summary 98
Focus on Problem Solving 99
Problems 100
Chapter 5 z-Scores: Location of Scores and Standardized Distributions 103
5.1 Overview 104
5.2 Introduction to z-Scores 104
5.3 z-Scores and Location in a Distribution 106
5.4 Using z-Scores to Standardize a Distribution 110
5.5 Other Standardized Distributions Based on z-Scores 113
Summary 116
Focus on Problem Solving 116
Problems 119
Chapter 6 Probability 121
6.1 Introduction to Probability 122
6.2 Probability and the Normal Distribution 127
Summary 139
Focus on Problem Solving 139
Problems 141
Chapter 7 Probability and Samples: The Distribution of Sample Means 144
7.1 Samples and Sampling Error 145
7.2 The Distribution of Sample Means 145
7.3 Probability and the Distribution of Sample Means 152
7.4 More about Standard Error 155
In the Literature: Reporting Standard Error 158
Summary 161
Focus on Problem Solving 161
Problems 163
Chapter 8 Introduction to Hypothesis Testing 166
8.1 The Logic of Hypothesis Testing 167
8.2 Uncertainty and Errors in Hypothesis Testing 176
8.3 An Example of a Hypothesis Test 180
In the Literature: Reporting the Results of the Statistical Test 182
8.4 Directional (One-Tailed) Hypothesis Tests 186
8.5 The General Elements of Hypothesis Testing: A Review 190
Summary 193
Focus on Problem Solving 194
Problems 196
Chapter 9 Introduction to the t Statistic 200
9.1 Overview 201
9.2 Hypothesis Tests with the t Statistic 207
In the Literature: Reporting the Results of a t Test 211
Summary 216
Focus on Problem Solving 217
Problems 219
Chapter 10 The t Test for Two Independent Samples 222
10.1 Overview 223
10.2 The t Statistic for an Independent-Measures Research Design 224
10.3 Hypothesis Tests with the Independent-Measures t Statistic 230
In the Literature: Reporting the Results of an Independent-Measures t Test 234
10.4 Assumptions Underlying the Independent-Measures t Formula 239
Summary 241
Focus on Problem Solving 242
Problems 244
Chapter 11 The t Test for Two Related Samples 249
11.1 Overview 250
11.2 The t Statistic for Related Samples 251
11.3 Hypothesis Tests for the Repeated-Measures Design 255
In the Literature: Reporting the Results of a Repeated-Measures t Test 258
11.4 Uses and Assumptions for Related-Samples t Tests 261
Summary 264
Focus on Problem Solving 265
Problems 268
Chapter 12 Estimation 272
12.1 An Overview of Estimation 273
12.2 Estimation with the t Statistic 278
12.3 A Final Look at Estimation 287
Summary 289
Focus on Problem Solving 290
Problems 294
Chapter 13 Introduction to Analysis of Variance 298
13.1 Introduction 299
13.2 The Logic of Analysis of Variance 302
13.3 ANOVA Notation and Formulas 306
13.4 The Distribution of F-Ratios 314
13.5 Examples of Hypothesis Testing with ANOVA 316
In the Literature: Reporting the Results of Analysis of Variance 319
13.6 Post Hoc Tests 327
Summary 333
Focus on Problem Solving 333
Problems 336
Chapter 14 More Advanced Analysis of Variance: Repeated-Measures and Two-Factor Designs 341
14.1 Overview 342
14.2 Repeated-Measures Analysis of Variance (ANOVA) 342
In the Literature: Reporting the Results of a Repeated-Measure ANOVA 353
14.3 Two-Factor Analysis of Variance (Independent Measures) 355
In the Literature: Reporting the Results of a Two-Factor ANOVA 369
Summary 373
Focus on Problem Solving 373
Problems 379
Chapter 15 Correlation and Regression 384
15.1 Introduction 385
15.2 The Pearson Correlation 388
15.3 Using and Interpreting the Pearson Correlation 393
15.4 Hypothesis Tests with the Pearson Correlation 399
In the Literature: Reporting Correlations 401
15.5 The Spearman Correlation 404
15.6 Introduction to Regression 410
Summary 417
Focus on Problem Solving 418
Problems 421
Chapter 16 The Chi-Square Statistic: Tests for Goodness of Fit and Independence 426
16.1 Parametric and Nonparametric Statistical Tests 427
16.2 The Chi-Square Test for Goodness of Fit 428
In the Literature: Reporting the Results for Chi-Square 436
16.3 The Chi-Square Test for Independence 438
16.4 Assumptions and Restrictions for Chi-Square Tests 448
Summary 449
Focus on Problem Solving 450
Problems 453
Appendix A Basic Mathematics Review 1
Appendix B Statistical Tables 24
Appendix C Solutions for Odd-Numbered Problems in the Text 35
Statistics Organizer 50
References 61
Index 62
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