Autorentext

R. BROOKE LEA, PhD, is DeWitt Wallace Professor of Psychology and Director of Cognitive Science at Macalester College in Saint Paul, MN, where he has taught psychological statistics for more than 25 years. He is a cognitive psychologist who studies reasoning and language processing, with a special interest in the role that poetic devices-such as rhyme, alliteration, and meter-play in the comprehension of poetry. BARRY H. COHEN, Ph.D. earned a B.S. in Physics and a Ph.D in experimental psychology. Until his retirement, he was the director of the MA program in psychology at NYU, and taught statistics and research design at the graduate level there for more than 30 years. He is now spending his active retirement by collaborating on meditation research.

Klappentext

The accessible, hands-on statistics textbook that behavioral science students and instructors trust Introductory Statistics for the Behavioral Sciences is a respected, practical textbook that offers carefully crafted exercises to support the teaching and learning of statistics. This revised eighth edition presents all the topics students in the behavioral sciences need in a uniquely accessible format, making statistics feel relevant and approachable. With fictitious yet realistic examples that reappear throughout the chapter, students can follow a continuous narrative that helps them engage with and internalize the content. User-friendly integration with SPSS software enables readers to gain hands-on experience with the application of theoretical concepts. Exercises at the end of each chapter, with additional practice in the online study guide, give students the repetition they need to fully comprehend the material. After working through this textbook, students will understand, not only the what, but also the why of statistical analysis.

• Get plain-English explanations of statistical concepts and procedures important in behavioral sciences research
• Learn from relatable examples and exercises focused on psychology, sociology, and other behavioral science
• Work through well-crafted exercises designed to enhance your understanding of the material

• Get clear instructions on how to perform statistical procedures with the industry-standard SPSS software Online resources for instructors include a test bank, chapter quizzes, and PowerPoint slides. Introductory Statistics for the Behavioral Sciences also includes a student website containing additional basic math coverage, math review exercises, a study guide, a set of additional SPSS exercises, and downloadable data sets.

  Inhalt

  Preface xi

  Acknowledgments xv

  Glossary of Symbols xvii

  Part I Descriptive Statistics 1

  Chapter 1 Introduction 3

  Why Study Statistics? 4

  Descriptive and Inferential Statistics 5

  Populations, Samples, Parameters, and Statistics 5

  Measurement Scales 6

  Independent and Dependent Variables 8

  Summation Notation 10

  Jackson's Study 14

  Summary 15

  Exercises 16

  Thought Questions 19

  Computer Exercises 19

  Bridge to SPSS 20

  Chapter 2 Frequency Distributions and Graphs 22

  Purpose of Descriptive Statistics 23

  Regular Frequency Distributions 23

  Cumulative Frequency Distributions 25

  Grouped Frequency Distributions 27

  Real and Apparent Limits 28

  Graphic Representations 29

  Skewing of Frequency Distributions 32

  Summary 34

  Exercises 35

  Thought Questions 36

  Computer Exercises 37

  Bridge to SPSS 37

  Chapter 3 Measures of Central Tendency and Variability 40

  Introduction 41

  The Mode 42

  The Median 43

  The Mean 44

  The Concept of Variability 47

  The Range 49

  The Standard Deviation and Variance 50

  Summary 55

  Exercises 57

  Thought Questions 58

  Computer Exercises 58

  Bridge to SPSS 59

  Chapter 4 Standardized Scores and the Normal Distribution 61

  Interpreting a Raw Score Revisited 62

  Rules for Changing and 63

  Standard Scores (z-Scores) 64
  T Scores, SAT Scores, and IQ Scores 67

  The Normal Distribution 68

  Table of the Standard Normal Distribution 70

  Illustrative Examples 71

  Summary 77

  Exercises 78

  Thought Questions 80

  Computer Exercises 80

  Bridge to SPSS 81

  Part II Basic Inferential Statistics 83

  Chapter 5 Introduction to Statistical Inference 85

  Introduction 86

  The Goals of Inferential Statistics 87

  Sampling Distributions 87

  The Standard Error of the Mean 93

  The z-Score for Sample Means 95

  Null Hypothesis Testing 96

  Assumptions Required by the Statistical Test for the Mean of a Single Population 103

  Why is Null Hypothesis Testing So Misunderstood? 104

  Summary 105

  Exercises 107

  Thought Questions 108

  Computer Exercises 108

  Bridge to SPSS 109

  Chapter 6 One-Sample t Test and Interval Estimation 110

  Introduction 110

  Statistical Test for the Mean of a Single Population When Is Not Known: The t Distributions 111

  Interval Estimation 115

  Computation 116

  Working with Proportions 118

  Summary 121

  Exercises 122

  Thought Questions 123

  Computer Exercises 123

  Bridge to SPSS 124

  Chapter 7 Testing Hypotheses About the Difference Between the Means of Two Populations 126

  The Standard Error of the Difference 127

  Estimating the Standard Error of the Difference 130

  The t Test for Two Independent Sample Means 131

  Confidence Intervals for 1 2 135

  Measuring the Size of an Effect for a Difference Between Two Independent Samples 136

  Reporting the Results of a t Test with a CI and a Measure of Effect Size 137

  The Assumptions Underlying the Proper Use of the t Test for Two Sample Means 138

  The t Test for Matched Samples 140

  Summary 146

  Exercises 148

  Thought Questions 150

  Computer Exercises 151

  Bridge to SPSS 151

  Chapter 8 Nonparametric Tests for the Difference Between Two Means 155

  Introduction 156

  The Difference Between the Locations of Two Independent Samples: The Rank-Sum Test 159

  The Difference Between the Locations of Two Matched Samples: The Wilcoxon Test 163

  Summary 167

  Exercises 169

  Thought Questions 172

  Computer Exercises 172

  Bridge to SPSS 172

  Chapter 9 Linear Correlation 175

  Introduction 176

  Describing the Linear Relationship Between Two Variables 178

  Interpreting the Magnitude of a Pearson r 184

  When Is It Important That Pearson's r Be Large? 190

  Testing the Significance of the Correlation Coefficient 191

  The Relationship Between Two Ranked Variables: The Spearman Rank-Order Correlation Coefficient 192

  Summary 195

  Exercises 196

  Thought Questions 199

  Computer Exercises 200

  Bridge to SPSS 200

  Appendix: Equivalence of the Various Formulas for r 203

  Chapter 10 Prediction and Linear Regression 205

  Introduction 206

  Using Linear Regression to Make Predictions 206

  Measuring Prediction Error: The Standard Error of Estimate 212

  The Connection Between Correlation and the t Test 214

  Estimating the Proportion of Variance Accounted for in the Population 219

  Summary 220

  Exercises 222

  Thought Questions 224

  Computer Exercises 224

  Bridge to SPSS 225

  Chapter 11 Introduction to Power Analysis 228

  Introduction 229

  Concepts of Power Analysis 230

  Power Analysis for the Mean of a Single Population 231

  Power Analysis for the Proportion of a Single Population 235

  Power Analysis for a Pearson r 236

  Power Analysis for the Difference Between Independent Means 237

  Power Analysis for the Difference Between the Means of Two Matched Populations 241

  Choosing a Value for d for a Power Analysis Involving Independent Means 242

  Using Power Analysis Concepts to Interpret the Results of Null Hypothesis Tests 243

  The Null Hypothesis Testing Controversy Revisited 244

  Summary 245

  Exercises 248

  Thought Questions 250

  Computer Exercises 250

  Bridge to SPSS 251

  Chapter 12 Beyond Traditional Null Hypothesis Testing 254

  More on Criticisms of NHT (and Some Rebuttals) 254

  Improving NHT with Robust Statistic…