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"Updated with the latest research, Gravetter/Wallnau/Forzano/Witnauer's ESSENTIALS OF STATISTICS FOR THE BEHAVIORAL SCIENCES, 10th Edition delivers straightforward instruction, hands-on learning tools and real-world examples to help you go beyond memorizing formulas to truly understanding the hows and whys of statistics. Giving extra focus to the topics students typically struggle with most, the authors take time to fully explain statistical concepts. Integrated applications reinforce concepts, offering further support to ensure that even those with a weak background in mathematics can fully grasp statistics. The authors also illustrate how an understanding of statistical procedures will help you comprehend published findings -- ultimately leading you to become a savvy consumer of information. Also available, the MindTap digital learning solution helps you learn on your own terms."-- From Amazon Cover......Page 1 Brief Contents......Page 5 Contents......Page 7 Preface......Page 15 About the Authors......Page 23 Chapter 1: Introduction to Statistics......Page 25 Preview......Page 26 1-1 Statistics and Behavioral Sciences......Page 27 1-2 Observations, Measurement, and Variables......Page 35 1-3 Three Data Structures, Research Methods, and Statistics......Page 43 1-4 Statistical Notation......Page 52 Summary......Page 56 Demonstration 1.1......Page 57 SPSS......Page 58 Problems......Page 62 Chapter 2: Frequency Distributions......Page 67 Preview......Page 68 2-1 Frequency Distributions and Frequency Distribution Tables......Page 69 2-2 Grouped Frequency Distribution Tables......Page 75 2-3 Frequency Distribution Graphs......Page 78 2-4 Stem and Leaf Displays......Page 86 Summary......Page 88 Demonstration 2.1......Page 89 Demonstration 2.2......Page 90 SPSS......Page 91 Problems......Page 94 Chapter 3: Central Tendency......Page 97 Preview......Page 98 3-1 Overview......Page 99 3-2 The Mean......Page 101 3-3 The Median......Page 109 3-4 The Mode......Page 114 3-5 Central Tendency and the Shape of the Distribution......Page 116 3-6 Selecting a Measure of Central Tendency......Page 118 Focus on Problem Solving......Page 125 SPSS......Page 126 Problems......Page 130 Chapter 4: Variability......Page 133 Preview......Page 134 4-1 Introduction to Variability......Page 135 4-2 Defining Variance and Standard Deviation......Page 140 4-3 Measuring Variance and Standard Deviation for a Population......Page 145 4-4 Measuring Variance and Standard Deviation for a Sample......Page 148 4-5 Sample Variance as an Unbiased Statistic......Page 154 4-6 More about Variance and Standard Deviation......Page 157 Key Terms......Page 165 Demonstration 4.1......Page 166 SPSS......Page 167 Problems......Page 169 Chapter 5: z-Scores: Location of Scores and Standardized Distributions......Page 173 Preview......Page 174 5-1 Introduction......Page 175 5-2 z- Scores and Locations in a Distribution......Page 176 5-3 Other Relationships between z, X, the Mean, and the Standard Deviation......Page 181 5-4 Using z-Scores to Standardize a Distribution......Page 184 5-5 Other Standardized Distributions Based on z-Scores......Page 188 5-6 Looking Ahead to Inferential Statistics......Page 191 Focus on Problem Solving......Page 194 Demonstration 5.2......Page 195 SPSS......Page 196 Problems......Page 198 Chapter 6: Probability......Page 201 Preview......Page 202 6-1 Introduction to Probability......Page 203 6-2 Probability and the Normal Distribution......Page 208 6-3 Probabilities and Proportions for Scores from a Normal Distribution......Page 216 6-4 Percentiles and Percentile Ranks......Page 222 6-5 Looking Ahead to Inferential Statistics......Page 227 Summary......Page 229 Demonstration 6.1......Page 230 SPSS......Page 231 Problems......Page 234 Chapter 7: Probability and Samples: The Distribution of Sample Means......Page 237 7-1 Samples, Populations, and the Distribution of Sample Means......Page 238 7-2 Shape, Central Tendency, and Variability for the Distribution of Sample Means......Page 243 7-3 z-Scores and Probability for Sample Means......Page 250 7-4 More about Standard Error......Page 254 7-5 Looking Ahead to Inferential Statistics......Page 259 Key Terms......Page 262 Demonstration 7.1......Page 263 Problems......Page 264 Chapter 8: Introduction to Hypothesis Testing......Page 267 8-1 The Logic of Hypothesis Testing......Page 268 8-2 Uncertainty and Errors in Hypothesis Testing......Page 280 8-3 More about Hypothesis Tests......Page 285 8-4 Directional (One-Tailed) Hypothesis Tests......Page 290 8-5 Concerns about Hypothesis Testing: Measuring Effect Size......Page 294 8-6 Statistical Power......Page 298 Summary......Page 307 Focus on Problem Solving......Page 308 Demonstration 8.2......Page 309 Demonstration 8.3......Page 310 Problems......Page 311 Chapter 9: Introduction to the t Statistic......Page 315 9-1 The t Statistic: An Alternative to z......Page 316 9-2 Hypothesis Tests with the t Statistic......Page 322 9-3 Measuring Effect Size for the t Statistic......Page 327 9-4 Directional Hypotheses and One-Tailed Tests......Page 336 Summary......Page 339 Demonstration 9.1......Page 340 SPSS......Page 341 Problems......Page 343 Chapter 10: The t Test for Two Independent Samples......Page 347 10-1 Introduction to the Independent-Measures Design......Page 348 10-2 The Hypotheses and the Independent-Measures t Statistic......Page 350 10-3 Hypothesis Tests with the Independent-Measures t Statistic......Page 358 10-4 Effect Size and Confidence Intervals for the Independent-Measures t......Page 364 10-5 The Role of Sample Variance and Sample Size in the Independent-Measures t Test......Page 369 Summary......Page 372 Demonstration 10.1......Page 373 SPSS......Page 375 Problems......Page 378 Chapter 11: The t Test for Two Related Samples......Page 383 11-1 Introduction to Repeated-Measures Designs......Page 384 11-2 The t Statistic for a Repeated-Measures Research Design......Page 386 11-3 Hypothesis Tests for the Repeated-Measures Design......Page 390 11-4 Effect Size, Confidence Intervals, and the Role of Sample Size and Sample Variance for the Repeated-Measures t......Page 393 11-5 Comparing Repeated- and Independent-Measures Designs......Page 399 Focus on Problem Solving......Page 404 Demonstration 11.1......Page 405 SPSS......Page 406 Problems......Page 408 Chapter 12: Introduction to Analysis of Variance......Page 415 12-1 Introduction: An Overview of Analysis of Variance......Page 416 12-2 The Logic of Analysis of Variance......Page 421 12-3 ANOVA Notation and Formulas......Page 425 12-4 Examples of Hypothesis Testing and Effect Size with ANOVA......Page 433 12-5 Post Hoc Tests......Page 440 12-6 More about ANOVA......Page 444 Summary......Page 449 Demonstration 12.1......Page 450 SPSS......Page 452 Problems......Page 455 Chapter 13: Two-Factor Analysis of Variance......Page 459 Preview......Page 460 13-1 An Overview of the Two-Factor, Independent- Measures ANOVA......Page 461 13-2 An Example of the Two-Factor ANOVA and Effect Size......Page 470 13-3 More about the Two-Factor ANOVA......Page 480 Summary......Page 486 Focus on Problem Solving......Page 487 Demonstration 13.1......Page 488 SPSS......Page 490 Problems......Page 495 Chapter 14: Correlation and Regression......Page 501 Preview......Page 502 14-1 Introduction......Page 503 14-2 The Pearson Correlation......Page 506 14-3 Using and Interpreting the Pearson Correlation......Page 511 14-4 Hypothesis Tests with the Pearson Correlation......Page 518 14-5 Alternatives to the Pearson Correlation......Page 522 14-6 Introduction to Linear Equations and Regression......Page 531 Summary......Page 544 Key Terms......Page 545 Demonstration 14.1......Page 546 SPSS......Page 548 Problems......Page 552 Chapter 15: The Chi-Square Statistic: Tests for Goodness of Fit and Independence......Page 557 15-1 Introduction to Chi-Square: The Test for Goodness of Fit......Page 558 15-2 An Example of the Chi-Square Test for Goodness of Fit......Page 564 15-3 The Chi-Square Test for Independence......Page 570 15-4 Effect Size and Assumptions for the Chi-Square Tests......Page 577 Summary......Page 582 Focus on Problem Solving......Page 583 Demonstration 15.1......Page 584 SPSS......Page 586 Problems......Page 589 Appendix A: Basic Mathematics Review......Page 593 Appendix B: Statistical Tables......Page 615 Appendix C: Solutions for Odd-Numbered Problems in the Text......Page 627 Appendix D: General Instructions for Using SPSS......Page 653 Statistics Organizer: Finding the Right Statistics for Your Data......Page 659 Summary of Statistics Formulas......Page 671 References......Page 675 Name Index......Page 681 Subject Index......Page 683 Cover 1 Brief Contents 5 Contents 7 Preface 15 About the Authors 23 Chapter 1: Introduction to Statistics 25 Preview 26 1-1 Statistics and Behavioral Sciences 27 1-2 Observations, Measurement, and Variables 35 1-3 Three Data Structures, Research Methods, and Statistics 43 1-4 Statistical Notation 52 Summary 56 Key Terms 57 Focus on Problem Solving 57 Demonstration 1.1 57 SPSS 58 Problems 62 Chapter 2: Frequency Distributions 67 Preview 68 2-1 Frequency Distributions and Frequency Distribution Tables 69 2-2 Grouped Frequency Distribution Tables 75 2-3 Frequency Distribution Graphs 78 2-4 Stem and Leaf Displays 86 Summary 88 Key Terms 89 Focus on Problem Solving 89 Demonstration 2.1 89 Demonstration 2.2 90 SPSS 91 Problems 94 Chapter 3: Central Tendency 97 Preview 98 3-1 Overview 99 3-2 The Mean 101 3-3 The Median 109 3-4 The Mode 114 3-5 Central Tendency and the Shape of the Distribution 116 3-6 Selecting a Measure of Central Tendency 118 Summary 125 Key Terms 125 Focus on Problem Solving 125 Demonstration 3.1 126 SPSS 126 Problems 130 Chapter 4: Variability 133 Preview 134 4-1 Introduction to Variability 135 4-2 Defining Variance and Standard Deviation 140 4-3 Measuring Variance and Standard Deviation for a Population 145 4-4 Measuring Variance and Standard Deviation for a Sample 148 4-5 Sample Variance as an Unbiased Statistic 154 4-6 More about Variance and Standard Deviation 157 Summary 165 Key Terms 165 Focus on Problem Solving 166 Demonstration 4.1 166 SPSS 167 Problems 169 Chapter 5: z-Scores: Location of Scores and Standardized Distributions 173 Preview 174 5-1 Introduction 175 5-2 z- Scores and Locations in a Distribution 176 5-3 Other Relationships between z, X, the Mean, and the Standard Deviation 181 5-4 Using z-Scores to Standardize a Distribution 184 5-5 Other Standardized Distributions Based on z-Scores 188 5-6 Looking Ahead to Inferential Statistics 191 Summary 194 Key Terms 194 Focus on Problem Solving 194 Demonstration 5.1 195 Demonstration 5.2 195 SPSS 196 Problems 198 Chapter 6: Probability 201 Preview 202 6-1 Introduction to Probability 203 6-2 Probability and the Normal Distribution 208 6-3 Probabilities and Proportions for Scores from a Normal Distribution 216 6-4 Percentiles and Percentile Ranks 222 6-5 Looking Ahead to Inferential Statistics 227 Summary 229 Key Terms 230 Focus on Problem Solving 230 Demonstration 6.1 230 SPSS 231 Problems 234 Chapter 7: Probability and Samples: The Distribution of Sample Means 237 Preview 238 7-1 Samples, Populations, and the Distribution of Sample Means 238 7-2 Shape, Central Tendency, and Variability for the Distribution of Sample Means 243 7-3 z-Scores and Probability for Sample Means 250 7-4 More about Standard Error 254 7-5 Looking Ahead to Inferential Statistics 259 Summary 262 Key Terms 262 Focus on Problem Solving 263 Demonstration 7.1 263 SPSS 264 Problems 264 Chapter 8: Introduction to Hypothesis Testing 267 Preview 268 8-1 The Logic of Hypothesis Testing 268 8-2 Uncertainty and Errors in Hypothesis Testing 280 8-3 More about Hypothesis Tests 285 8-4 Directional (One-Tailed) Hypothesis Tests 290 8-5 Concerns about Hypothesis Testing: Measuring Effect Size 294 8-6 Statistical Power 298 Summary 307 Key Terms 308 Focus on Problem Solving 308 Demonstration 8.1 309 Demonstration 8.2 309 Demonstration 8.3 310 SPSS 311 Problems 311 Chapter 9: Introduction to the t Statistic 315 Preview 316 9-1 The t Statistic: An Alternative to z 316 9-2 Hypothesis Tests with the t Statistic 322 9-3 Measuring Effect Size for the t Statistic 327 9-4 Directional Hypotheses and One-Tailed Tests 336 Summary 339 Key Terms 340 Focus on Problem Solving 340 Demonstration 9.1 340 Demonstration 9.2 341 SPSS 341 Problems 343 Chapter 10: The t Test for Two Independent Samples 347 Preview 348 10-1 Introduction to the Independent-Measures Design 348 10-2 The Hypotheses and the Independent-Measures t Statistic 350 10-3 Hypothesis Tests with the Independent-Measures t Statistic 358 10-4 Effect Size and Confidence Intervals for the Independent-Measures t 364 10-5 The Role of Sample Variance and Sample Size in the Independent-Measures t Test 369 Summary 372 Key Terms 373 Focus on Problem Solving 373 Demonstration 10.1 373 Demonstration 10.2 375 SPSS 375 Problems 378 Chapter 11: The t Test for Two Related Samples 383 Preview 384 11-1 Introduction to Repeated-Measures Designs 384 11-2 The t Statistic for a Repeated-Measures Research Design 386 11-3 Hypothesis Tests for the Repeated-Measures Design 390 11-4 Effect Size, Confidence Intervals, and the Role of Sample Size and Sample Variance for the Repeated-Measures t 393 11-5 Comparing Repeated- and Independent-Measures Designs 399 Summary 404 Key Terms 404 Focus on Problem Solving 404 Demonstration 11.1 405 Demonstration 11.2 406 SPSS 406 Problems 408 Chapter 12: Introduction to Analysis of Variance 415 Preview 416 12-1 Introduction: An Overview of Analysis of Variance 416 12-2 The Logic of Analysis of Variance 421 12-3 ANOVA Notation and Formulas 425 12-4 Examples of Hypothesis Testing and Effect Size with ANOVA 433 12-5 Post Hoc Tests 440 12-6 More about ANOVA 444 Summary 449 Key Terms 450 Focus on Problem Solving 450 Demonstration 12.1 450 Demonstration 12.2 452 SPSS 452 Problems 455 Chapter 13: Two-Factor Analysis of Variance 459 Preview 460 13-1 An Overview of the Two-Factor, Independent- Measures ANOVA 461 13-2 An Example of the Two-Factor ANOVA and Effect Size 470 13-3 More about the Two-Factor ANOVA 480 Summary 486 Key Terms 487 Focus on Problem Solving 487 Demonstration 13.1 488 SPSS 490 Problems 495 Chapter 14: Correlation and Regression 501 Preview 502 14-1 Introduction 503 14-2 The Pearson Correlation 506 14-3 Using and Interpreting the Pearson Correlation 511 14-4 Hypothesis Tests with the Pearson Correlation 518 14-5 Alternatives to the Pearson Correlation 522 14-6 Introduction to Linear Equations and Regression 531 Summary 544 Key Terms 545 Focus on Problem Solving 546 Demonstration 14.1 546 SPSS 548 Problems 552 Chapter 15: The Chi-Square Statistic: Tests for Goodness of Fit and Independence 557 Preview 558 15-1 Introduction to Chi-Square: The Test for Goodness of Fit 558 15-2 An Example of the Chi-Square Test for Goodness of Fit 564 15-3 The Chi-Square Test for Independence 570 15-4 Effect Size and Assumptions for the Chi-Square Tests 577 Summary 582 Key Terms 583 Focus on Problem Solving 583 Demonstration 15.1 584 Demonstration 15.2 586 SPSS 586 Problems 589 Appendixes 593 Appendix A: Basic Mathematics Review 593 Appendix B: Statistical Tables 615 Appendix C: Solutions for Odd-Numbered Problems in the Text 627 Appendix D: General Instructions for Using SPSS 653 Statistics Organizer: Finding the Right Statistics for Your Data 659 Summary of Statistics Formulas 671 References 675 Name Index 681 Subject Index 683 Statistics is one of the most practical and essential courses that you will take, and a primary goal of this popular text is to make the task of learning statistics as simple as possible. Straightforward instruction, built-in learning aids, and real-world examples have made STATISTICS FOR THE BEHAVIORAL SCIENCES, 10th Edition the text selected most often by instructors for their students in the behavioral and social sciences. The authors provide a conceptual context that makes it easier to learn formulas and procedures, explaining why procedures were developed and when they should be used. This text will also instill the basic principles of objectivity and logic that are essential for science and valuable in everyday life, making it a useful reference long after you complete the course.