Experimental Psychology PDF - Ninth Edition

Experimental Psychology NINTH EDITION Barry. H. Kantowitz University of Michigan Henry L. Roediger III Washington University in St. Louis David G. Elmes Washington and Lee University Australia Brazil...

Experimental Psychology NINTH EDITION Barry. H. Kantowitz University of Michigan Henry L. Roediger III Washington University in St. Louis David G. Elmes Washington and Lee University Australia Brazil Japan Korea Mexico Singapore Spain United Kingdom United States Experimental Psychology, Ninth Edition © 2009, 2005 Wadsworth, Cengage Learning Barry H. Kantowitz, Henry L. Roediger III, ALL RIGHTS RESERVED. No part of this work covered by the copyright David G. Elmes herein may be reproduced, transmitted, stored, or used in any form or by Publisher: Michele Sordi any means graphic, electronic, or mechanical, including but not limited to photocopying, recording, scanning, digitizing, taping, Web distribution, Assistant Editor: Rebecca Rosenberg information networks, or information storage and retrieval systems, except Technology Project Manager: Lauren Keyes as permitted under Section 107 or 108 of the 1976 United States Copyright Marketing Manager: Michelle Williams Act, without the prior written permission of the publisher. 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Locate your local office at (main image) and © Akira Inoue/Getty international.cengage.com/region. Images (inset image) Compositor: Graphic World Inc. Cengage Learning products are represented in Canada by Nelson Education, Ltd. For your course and learning solutions, visit academic.cengage.com. Purchase any of our products at your local college store or at our preferred online store www.ichapters.com. Printed in the United States of America 1 2 3 4 5 6 7 12 11 10 09 08 To three outstanding psychologists who shared the fun and excitement of experimental psychology with us, David A. Grant, William M. Hinton, and L. Starling Reid This page intentionally left blank ABOUT THE AUTHORS BARRY H. KANTOWITZ is Professor of Psychology, Professor of Industrial and Operational Engineering, and former Direc- tor of the Transportation Research Institute at the University of Michigan. Prior to that, he was Chief Scientist of the Human Fac- tors Transportation Center of the Battelle Memorial Institute in Seattle. He received the Ph.D. degree in experimental psychol- ogy from the University of Wisconsin in 1969. From 1969 to 1987 he held positions as Assistant, Associate, and Professor of Psy- chological Sciences at Purdue University, West Lafayette, Indiana. Dr. Kantowitz was elected a Fellow of the American Psychological Association in 1974. He has been a National Institute of Mental Health Postdoctoral Fellow at the University of Oregon, a Senior Lecturer in Ergonomics at the Norwegian Institute of Technology, Trondheim, Norway, and a Visiting Professor of Technical Psychology at the Uni- versity of Lulea, Sweden. He has written and edited more than one dozen books. His research on human attention, mental workload, reaction time, human-machine interaction, and human factors has been supported by the Office of Education, the National Institute of Mental Health, the National Aeronautics and Space Administration, the Air Force Office of Scientific Research, and the Federal High- way Administration. He has served as editor of the Transportation Human Factors Journal, Associate Editor of Human Factors, and edits the book series Human Factors in Transportation. HENRY L. ROEDIGER III is the James S. McDonnell University Distinguished University Professor of Psychology and Dean of Academic Planning at Washington University in St. Louis, where he has taught since 1996. He received a B.A. degree in psychology from Washington and Lee University in 1969 and a Ph.D. in cog- nitive psychology from Yale University in 1973. He has taught at Rice University (1988–1996) and Purdue University (1973–1988) and spent 3 years as a visiting professor at the University of Toronto. His research interests lie in cognitive psychology, particularly in human learning and memory. Dr. Roediger has published over 180 articles, chapters, and reviews, v vi ABOUT THE AUTHORS as well as two other textbooks: Psychology (coauthored with E. D. Capaldi, S. G. Paris, J. Polivy, and P. Herman) and Research Methods in Psychology (with D. G. Elmes and B. H. Kantowitz). He also co-edited Varieties of Memory and Consciousness: Essays in Honour of Endel Tulving (1989) and The Science of Memory: Concepts (2007), as well as several other books. Dr. Roediger has served as editor of the Journal of Experimen- tal Psychology: Learning, Memory and Cognition (1984–1989) and was the founding editor of Psychonomic Bulletin & Review (1994-1997). He is a consulting editor for nine journals, including Psychological Science, the Journal of Experimental Psychology: Learning, Memory, and Cognition, the Journal of Memory and Language, and Memory, among others. He has served as President of the American Psychological Society, the Midwest Psychological Association, and the Experimental Psychology Division of the American Psychological Association. He was a member of the Governing Board of the Psychonomic Society for 5 years and its Chair in 1989–1990. He has been named a Highly Cited Researcher by the Institute of Scientific Information and also received a Guggenheim Fellowship. Roediger has been elected to membership in the Society of Experimental Psychologists and the American Academy of Arts and Sciences, as well as being elected Fellow of the American Association for the Advancement of Science, the American Psychological Association, the Association for Psychological Science, and the Canadian Psychological Association. DAVID G. ELMES is Professor Emeritus of Psychology at Washington and Lee University, where he taught for 40 years. He earned his B.A. with high honors from the Uni- versity of Virginia and completed the M.A. and Ph.D. degrees in psychology there. Dr. Elmes was an adjunct professor at Hampden-Sydney College, was a research associate for a year in the Human Performance Center of the University of Michigan, and was a Visiting Fellow of University College at the University of Oxford. At Washington and Lee, he codirected the Cognitive Science Program for 14 years and chaired the Department of Psychology for ten years. Pro- fessor Elmes edited Readings in Experimental Psychology, Directory of Research in Psychology at Primarily Undergraduate Institutions, and is coauthor of the eighth edition of Research Methods in Psychology (2006, with B. H. Kantowitz and H. L. Roediger III). Dr. Elmes has published numerous articles concerned with human and animal learning, memory, and the sense of smell. The smell research has been supported by the National Institute of Environmental Health Sciences. He frequently referees papers submitted to technical journals and was a consulting editor for the Jour- nal of Experimental Psychology: Learning, Memory and Cognition for several years. Professor Elmes is passionate about the educational value of undergraduate research. For a number of years he was active in the Council of Undergraduate Research, for which he has served as Psychology Councilor, Psychology Division Chair, and President. Dr. Elmes is a fellow of the Association for Psychological Science. CONTENTS IN BRIEF ▼ PART ONE FUNDAMENTALS OF RESEARCH 1 Chapter 1 Explanation in Scientific Psychology 3 Chapter 2 Research Techniques: Observation and Correlation 24 Chapter 3 Research Techniques: Experiments 51 Chapter 4 Ethics in Psychological Research 82 Chapter 5 How to Read and Write Research Reports 99 ▼ PART TWO PRINCIPLES AND PRACTICES OF EXPERIMENTAL PSYCHOLOGY 151 Chapter 6 Psychophysics 153 Chapter 7 Perception 180 Chapter 8 Attention and Reaction Time 207 Chapter 9 Conditioning and Learning 227 Chapter 10 Remembering and Forgetting 261 Chapter 11 Thinking and Problem Solving 297 Chapter 12 Individual Differences and Development 327 Chapter 13 Social Psychology 358 Chapter 14 Environmental Psychology 388 Chapter 15 Human Factors 410 vii This page intentionally left blank CONTENTS ▼ PART ONE FUNDAMENTALS OF RESEARCH 1 CHAPTER 1 EXPLANATION IN SCIENTIFIC PSYCHOLOGY 3 Making Sense of the World 4 Social Loafing 4 Curiosity: The Wellspring of Science 5 Sources of Knowledge 6 Fixation of Belief 6 The Nature of the Scientific Explanation 8 What Is a Theory? 8 Induction and Deduction 9 From Theory to Hypothesis 12 Evaluating Theories 14 Intervening Variables 15 Foxes and Hedgehogs Roaming through Psychological Theory 17 The Science of Psychology 18 Psychology and the Real World 19 Summary 22 Key Terms 23 Discussion Questions 23 Web Connections 23 CHAPTER 2 RESEARCH TECHNIQUES: OBSERVATION AND CORRELATION 24 Naturalistic Observation 26 What Do We Observe? 28 Reactivity 30 The Case Study 31 Survey Research 32 Advantages and Disadvantages of Naturalistic Observations 33 The Relational Approach 36 Contingency Research 36 Correlational Research 38 The Correlation Coefficient 38 Complex Correlational Procedures 44 ix x CONTENTS Cause: A Note 46 Summary 48 Key Terms 49 Discussion Questions 49 Web Connections 50 Laboratory Resource 50 CHAPTER 3 RESEARCH TECHNIQUES: EXPERIMENTS 51 What Is an Experiment? 52 Advantages of Experiments 53 Why Experiments Are Conducted 54 Variables 55 Independent Variables 55 Dependent Variables 56 Control Variables 57 Name the Variables 57 More Than One Independent Variable 58 More Than One Dependent Variable 63 Experimental Designs 64 Between-Subjects Designs 64 Within-Subjects Designs 65 Small-n Designs 66 Mixed Designs 67 Control Conditions 67 Pitfalls 68 Quasi-Experiments 71 From Problem to Experiment: The Nuts and Bolts 76 Conducting an Experiment 76 From Problem to Experiment 76 Data 77 Obtaining Data 77 Analyzing Data 78 Reporting Data 78 Summary 79 Key Terms 80 Discussion Questions 81 Web Connections 81 CHAPTER 4 ETHICS IN PSYCHOLOGICAL RESEARCH 82 Research with Human Participants 83 Informed Consent and Deception 85 Freedom to Withdraw 86 Protection from Harm and Debriefing 87 Removing Harmful Consequences 87 Confidentiality 88  CONTENTS xi Ethics in Research with Animals 89 Arguments against Research with Animals 89 Arguments for Research with Animals 90 Guidelines for Use of Animals in Research 91 Scientific Fraud 92 Monitoring Ethical Practices 94 Summary 95 Key Terms 96 Discussion Questions 96 Web Connections 96 Suggested Readings 97 Psychology in Action: Understanding and Remembering Consent Forms 97 CHAPTER 5 HOW TO READ AND WRITE RESEARCH REPORTS 99 How to Do a Literature Search 100 The Parts of an Article 101 Title and Author(s) 101 Abstract 101 Introduction 102 Method 102 Results 102 Discussion 105 References 105 Checklist for the Critical Reader 105 Introduction 106 Method 106 Results 107 Discussion 107 Checklist Summary 108 A Sample Journal Article 109 Writing a Research Report 118 Format 119 Sample Manuscript 121 Style 143 Publishing an Article 146 Summary 147 Key Terms 147 Web Connections 148 Laboratory Resource 148 Psychology in Action: A Literature Search 148 xii CONTENTS ▼ PART TWO PRINCIPLES AND PRACTICES OF EXPERIMENTAL PSYCHOLOGY 151 CHAPTER 6 PSYCHOPHYSICS 153 Measuring Sensations 154 6.1 Experimental Topics and Research Illustrations Operational Definition: Thresholds 156 Introducing the Variables 157 6.2 Experimental Topics and Research Illustrations Measurement Scales: Fechner’s Law and Stevens’ Law 169 6.3 Experimental Topics and Research Illustrations Small-n Design: Psychophysical Methods 174 From Problem to Experiment: The Nuts and Bolts Do Pigeons Have Visual Thresholds? 176 Summary 177 Key Terms 177 Discussion Questions 178 Web Connections 178 Psychology in Action: Weber’s Law 178 CHAPTER 7 PERCEPTION 180 Issues in Perception 181 Direct and Indirect Perception 181 Awareness and Perception 183 Introducing the Variables 186 7.1 Experimental Topics and Research Illustrations Verbal Report: Perception without Awareness 187 7.2 Experimental Topics and Research Illustrations Converging Operations: Perception without Awareness and Perception with Explicit Awareness 196 From Problem to Experiment: The Nuts and Bolts The Color–Distance Illusion 201 Summary 204 Key Terms 205 Discussion Questions 205 Web Connections 205 Laboratory Resource 205 Psychology in Action: The Stroop Effect 206 CHAPTER 8 ATTENTION AND REACTION TIME 207 The ABC of Reaction Time 208 8.1 Experimental Topics and Research Illustrations Confounding: Pure Insertion 210 Introducing the Variables 211  CONTENTS xiii 8.2 Experimental Topics and Research Illustrations Selection of the Dependent Variable: Speed–Accuracy Trade-Off 215 8.3 Experimental Topics and Research Illustrations Interaction Effects: Cognitive Control 221 From Problem to Experiment: The Nuts and Bolts Measuring Attention 222 Summary 225 Key Terms 225 Discussion Questions 225 Web Connections 226 Psychology in Action: Speed–Accuracy Trade-Off 226 CHAPTER 9 CONDITIONING AND LEARNING 227 Types of Conditioning 229 Classical Conditioning: Does the Name Pavlov Ring a Bell? 229 Instrumental (Operant) Conditioning 231 Introducing the Variables 234 9.1 Experimental Topics and Research Illustrations Within- and Between-Subjects Designs: Stimulus Intensity 235 9.2 Experimental Topics and Research Illustrations Counterbalancing: Simultaneous Contrast 240 9.3 Experimental Topics and Research Applications Small-n Designs: Behavior Problems in Children 246 From Problem to Experiment: The Nuts and Bolts The Partial Reinforcement Extinction Effect 253 Summary 257 Key Terms 258 Discussion Questions 258 Web Connections 259 Psychology in Action: Knowledge of Results as Reinforcement 259 CHAPTER 10 REMEMBERING AND FORGETTING 261 Ebbinghaus’s Contribution—When Memory Was Young 262 Varieties of Memory 266 Introducing the Variables 267 10.1 Experimental Topics and Research Illustrations Scale Attenuation: Modality Differences 268 10.2 Experimental Topics and Research Illustrations Generality of Results: Levels of Processing 274 10.3 Experimental Topics and Research Illustrations Interaction Effects: Implicit and Explicit Memory Tests 281 From Problem to Experiment: The Nuts and Bolts Which Is More Effective, Reading or Listening? 291 xiv CONTENTS Summary 293 Key Terms 294 Discussion Questions 295 Web Connections 295 Laboratory Resources 295 Psychology in Action: Remembering the 9/11 Terrorist Attacks 296 CHAPTER 11 THINKING AND PROBLEM SOLVING 297 Two Approaches to Thinking 299 Thorndike’s Trial-and-Error Learning 299 Insight in Köhler’s Chimpanzees 300 11.1 Experimental Topics and Research Illustrations Reliability and Replication: Analogical Reasoning 301 Introducing the Variables 303 11.2 Experimental Topics and Research Illustrations Experimental Control: Functional Fixedness 311 11.3 Experimental Topics and Research Illustrations Verbal Reports: Overconfidence in Judgments 315 From Problem to Experiment: The Nuts and Bolts Incubation in Problem Solving 319 Summary 323 Key Terms 323 Discussion Questions 324 Web Connections 325 Psychology in Action: Confirmation Bias 325 CHAPTER 12 INDIVIDUAL DIFFERENCES AND DEVELOPMENT 327 Approaches to Individual Differences 329 Methodological Approaches to Individual Differences 329 Variables Leading to Individual Differences 330 Introducing the Variables 332 12.1 Experimental Topics and Research Illustrations Reliability of Measures: Intelligence and Developmental Research Designs 333 12.2 Experimental Topics and Research Illustrations Operational Definitions: Intelligence 339 12.3 Experimental Topics and Research Illustrations Regression Artifacts: Educational Assessment 345 From Problem to Experiment: The Nuts and Bolts What Roles Do Motivation and Emotion Play in Intellectual Performance? 350 Summary 354 Key Terms 355 Discussion Questions 355 Web Connections 356 Psychology in Action: A Demonstration of Regression Artifacts 356  CONTENTS xv CHAPTER 13 SOCIAL PSYCHOLOGY 358 The Origins of Social Psychology 359 13.1 Experimental Topics and Research Illustrations Experimental Control: Obedience to Authority 362 Introducing the Variables 363 Conditions Encouraging Obedience 367 13.2 Experimental Topics and Research Illustrations Demand Characteristics and Experimenter Bias: Hypnosis 370 13.3 Experimental Topics and Research Illustrations Field Research: Bystander Intervention 374 13.4 Experimental Topics and Research Illustrations Choosing the Dependent Variable: Measuring Stereotypes and Prejudice 378 From Problem to Experiment: The Nuts and Bolts How Does the Presence of Other People Affect an Individual’s Performance on a Task? 381 Summary 384 Key Terms 385 Discussion Questions 385 Web Connections 386 Laboratory Resources 386 Psychology in Action: The Power of Being in an Experiment 386 CHAPTER 14 ENVIRONMENTAL PSYCHOLOGY 388 Is Science the Only Path to Truth? 389 Discovering the Truth about City Life 391 14.1 Experimental Topics and Research Illustrations Generalization of Results: Crowding 393 Introducing the Variables 394 14.2 Experimental Topics and Research Illustrations Quasi-Experiments: Noise and Cognitive Performance 401 14.3 Experimental Topics and Research Illustrations Ethical Issues: Deception and Concealment 403 From Problem to Experiment: The Nuts and Bolts Is Exposure to Noise Bad for You? 405 Summary 407 Key Terms 408 Discussion Questions 408 Web Connections 408 Laboratory Resources 408 Psychology in Action: Noise and Memory 409 CHAPTER 15 HUMAN FACTORS 410 Human Factors and Human Behavior 411 Definition 411 Honor Thy User 412 The Value of Life 413 xvi CONTENTS Introducing the Variables 414 15.1 Experimental Topics and Research Illustrations Small-n Design: Dynamic Visual Acuity 415 15.2 Experimental Topics and Research Illustrations Selection of Dependent Variable: Mental Workload 417 15.3 Experimental Topics and Research Illustrations Field Research: The Centered High-Mounted Brake Light 425 From Problem to Experiment: The Nuts and Bolts Measure Pilot Mental Workload in Flight 427 Summary 428 Key Terms 428 Discussion Questions 429 Web Connections 429 Psychology in Action: Understanding Traffic Sign Symbols 429 APPENDIX A EXPERIMENTAL PSYCHOLOGY: A HISTORICAL SKETCH 432 Origins of Experimental Psychology: Philosophy and Physiology 433 The Contribution of Helmholtz 435 Early Scientific Psychology 435 Ernst Weber 436 Gustav Fechner 436 Wilhelm Wundt 437 Hermann Ebbinghaus 437 Schools of Psychology 438 Structuralism: The Structure of Mental Life 438 Functionalism: The Uses of Mind 439 Behaviorism: Rejecting Mental Explanations 440 Gestalt Psychology: Perception of the Whole 441 Some Modern Trends 442 World War II and the Extension of Psychology 442 Cognitive Psychology: The Return of Mind 442 Cognitive Neuroscience: The Decade of the Brain 443 Specialization 444 Summary 446 Key Terms 447 Web Connections 447 APPENDIX B STATISTICAL REASONING: AN INTRODUCTION 448 Descriptive Statistics: Telling It Like It Is 449 Central Tendency 450 Measures of Dispersion 451 A Note on Calculation 453 The Normal Distribution 454 Correlation Coefficient 456  CONTENTS xvii Inferential Statistics 458 Sampling 458 The Distribution of Sample Means 460 Testing Hypotheses 463 Tests for Differences between Two Groups 469 t Test 473 Magnitude of Effect 476 The Analysis of Variance 477 ␹2 Test for Independence 486 Misuses of Statistics 487 Use of Small or Biased Samples 488 Absent or Inappropriate Comparisons 489 The Gambler’s Fallacy 490 Summary 491 Key Terms 492 Web Connections 492 APPENDIX C STATISTICAL TABLES 494 Table A Proportions of Area under the Normal Curve 495 Table B Critical Values of the U Statistic of the Mann-Whitney Test 498 Table C Distribution for the Sign Test 500 Table D Critical Values of Wilcoxon’s T Statistic for the Matched-Pairs Signed-Ranks Test 502 Table E Critical Values of t 503 Table F Critical Values of the F Distribution 504 Table G Critical Values of the ␹2 Distribution 508 Table H Random Numbers 509 REFERENCES 511 GLOSSARY 528 NAME INDEX 542 SUBJECT INDEX 545 This page intentionally left blank PREFACE The term experimental psychology used to denote only a few selected topics in psychology. In, say, 1930, experiments were conducted to understand sensation, perception, learning, memory, and a few other topics. The situation is quite different today: Experimental methods are used to investigate social psy- chology, developmental psychology, individual differences, and many other topics (such as environmental psychology) that were not considered in psychology’s vision eighty years ago. The use of experimental methods has expanded to include most topics in the field. Writing a textbook aimed at this topic has therefore become an increasing challenge. This textbook is the ninth edition of a book first published in 1978. Each edition has seen both major and minor changes in response to students’ and professors’ comments, and this edition is no exception. Readers familiar with the previous edition will find changes in every chapter. We have tried to blend the best aspects of the previous eight editions with new features to make the book even more appealing. (We describe the changes in more detail below.) We are pleased that the continued popularity of this text has permitted us to produce this new edition, because we think we have been able to improve it, and we have enjoyed working on it again. The title Experimental Psychology has appeared on many text- books that have become classics, beginning with E. B. Titchener’s pair in the early 1900s, through Woodworth’s 1928 text and its revision (Woodworth & Schlossberg, 1954), and finally to those books by Osgood (1953) and Underwood (1966). All these books provided an introduction to research methodology, but they did so in the context of fundamental research in experimental psychol- ogy. The books were primarily about the content of experimental psychology, with an emphasis on the research methods used to acquire the knowledge. We see our textbook as firmly within this tradition, even if much less encyclopedic than the great books mentioned above. Today this approach is unique; during the 1970s and the 1980s, many “research methods” texts appeared that orga- nize the subject matter quite differently. Instead of providing xix xx PREFACE methodology in the context in which it is used, these books treat methodological topics (e.g., between-subjects designs, small-n designs) as chapter titles and in- troduce content examples to flesh out the discussion of the methods. This is also an excellent approach, and we have produced another text that embodies this method (Research Methods in Psychology, by Elmes, Kantowitz, and Roediger, also published by Wadsworth). However, Experimental Psychology seeks to provide an integrated blend of content and methodology, with methods discussed in the con- text of actual research. Primary differences between our text and those of our prede- cessors in this tradition are that our approach is to select particular examples that best illustrate the methodological point under consideration and that our book is intended mostly for an undergraduate audience with only a first course in psychology as a background. We should note one point about terms in our book. In 1994, the Publication Manual of the American Psychological Association recommended that the traditional term subjects, which had been used for over a century to refer to people who were tested in psychological research, be changed to participants. This change received a mixed reaction in the research community, and some other organizations that publish psychology journals did not go along. For example, the Psychonomic Soci- ety permits use of either term in papers published in their journals. In addition, the copyeditors of the American Psychological Association journals do not insist that participants be used as the favored term, but rather encourage its use. Because the situation is unsettled, we have followed the convention of using both subjects and participants when referring to people in psychological research. We tend to use subjects when referring to non-human animals in research, but we use both terms when referring to humans. The usage in our text therefore reflects current practice in the field at large. ▼ TEXT ORGANIZATION The philosophy of the text remains unchanged. As with the first eight editions, we have striven to achieve an integrated treatment of experimental psychology with a seamless link binding methodology and content. The book includes two main parts. The first five chapters constitute Part One, Fundamentals of Research, and discuss some basic methodological preliminaries that students need. In these chapters we describe some general aspects of science and theory construction; the features of (and differences among) observational, correlational, and experimental methods (with an emphasis on the last); ethical issues in research; and how to read and write research reports. In the remaining ten chapters, which make up Part Two, Principles and Practices of Research, we flesh out the bare bones provided in Part One by illustrating method- ological topics in the context of actual research problems. The chapters are provided with content titles (for example, Perception), and some content is covered in its own right, but the main purpose of the chapters is to present methodological topics in the context of actual research. This organization reflects our belief that the best way to provide students with an understanding of methodology is to embed it in the context of real problems that occur in conducting research. Methodology does not exist in a vacuum, but is devised to solve concrete research problems. We hope that presenting  PREFACE xxi methods in the context of important content issues will help students to see the impor- tance of considering research methods. Chapter Format The chapters in Part Two all share a common format. This parallel structure should help orient students to important features of the text that facilitate learning. Chapter Opening The chapters begin with an outline and quotation. Following a brief orientation to the content area explored in the chapter, the student will come across the first of several boxed inserts, which readers of the previous editions have found to be helpful and which have therefore been carried over to the ninth edition. Introducing the Variables This feature quickly orients the student to those indepen- dent, dependent, and control variables commonly used in particular research areas. Our coverage of these variables does not exhaust the possibilities, but does include some of the most common ones. Experimental Topics and Research Illustrations This feature represents the main part of the chapter, in which two or three methodology issues are presented in the context of an actual research problem. Thus, for example, in Chapter 10 we discuss the dif- ficulty of ceiling and floor effects in the context of a memory experiment in which this problem actually arose. Many of these experimental topics have been introduced in Part One and are covered in more detail in Part Two. Some crucial topics are dis- cussed more than once in Part Two to ensure better comprehension. The content top- ics were chosen to be good vehicles for discussing the particular methodological point under consideration. Thus, the content topics may not represent the most important topics in the subject under discussion, nor do we intend our chapters to represent a complete summary of contemporary work in the area. Our intent is to illustrate issues of methods in the context of actual research problems that are of interest. Two other unique features appear toward the end of each chapter in Part Two. From Problem To Experiment: The Nuts and Bolts In this section, we present the rationale behind experimental design decisions—how many subjects should be used, why variable X is selected instead of variable Y, and so on—when hypotheses are taken from a general form to the specifics of an experiment. These decisions are the “nuts and bolts” of experi- mental research. They are second nature to practicing experimenters and hence seldom articulated in journal articles, but they may represent puzzles to those new to research. Psychology in Action This feature suggests safe and simple experimental demonstra- tions that require little or no equipment and that can be used in or out of class. For ex- ample, Chapter 7 includes a demonstration of the Stroop effect and Chapter 14 presents methods to measure the effects of noise on memory. End-of-Chapter Features Finally each chapter contains a summary in which the main points of the chapter are reviewed, a set of key terms for review and study, and several discussion questions. xxii PREFACE Chapter Sequence Although students will be best served by reading Part One in correct serial order (espe- cially the first three chapters), those professors and students more interested in methodol- ogy than in content can ignore the chapter numbers in Part Two. The table that cross-lists chapter numbers and experimental topics (to be found after the Preface) can be used to determine the order in which chapters in Part Two are assigned. Thus, the instructor has the option of following a more- or less-traditional order or of creating a unique ordering better suited to his or her educational goals. Two lesser-used chapters that, however, may be quite necessary for some, are located in appendixes. Appendix A provides a brief sketch of the history of experimental psychology, and Appendix B contains a review of basic statistics. Ancillaries Ancillaries for this edition include the following: Instructor’s Manual with Test Bank Resources for instructors include chapter outlines, key terms, answers to discussion questions, lecture suggestions, demonstration sugges- tions, and “experimental dilemmas.” The test bank contains multiple-choice, true-false, and essay questions for each chapter. The test bank is also available electronically in the ExamView® format for the instructors to create their own tests/answers. Electronic Transparencies Many of the figures from the text are available as Power- Point® slides that can be downloaded and used in the classroom. Book Companion Website academic.cengage.com/psychology/kantowitz The website contains several helpful features for both instructors and students. Instructors will be able to find teaching activities, chapter outlines, and chapters summaries. To aid stu- dents, the website contains a glossary, flashcards, crossword puzzles to help learn key terms, and web links to Wadsworth Online Research Methods workshops, as well as other useful web links; suggestions for using Infotrac College Edition; and multiple- choice, matching, fill-in-the-blank, and essay tutorial quizzes that can be printed out or emailed directly to instructors. Changes in the Ninth Edition Users of the previous edition will discover many changes in the current edition. Web references have been updated for all chapters; while these were working in January 2008, some will undoubtedly change during the life of this edition. These references guide readers to relevant discussions online, including the Wadsworth Online at The Wadsworth Psychology Study Center. In addition, instructors in North America who have specified that InfoTrac College Edition be packaged with this text have been pro- vided 4 months of free access to this extensive virtual library for their students. New coverage and more recent references have been added in every chapter, and some chapters have been rebuilt to reflect the most recent findings and topics,  PREFACE xxiii even though this meant removing substantial amounts of text dearly cherished by the authors. Chapter 1 adds new research on the dangers of using a cell phone while driv- ing, and the section on relationships between applied and basic research has been updated to cover recent developments in the push to translate basic findings into appli- cations at NIH. Chapter 2 contains new data in Table 2-1 and new discussion that media violence is a threat to public health, and the chapter now discusses the attitudes of voters toward the appearance of presidential candidates on late-night comedy shows. Chapter 3 has a new and more interesting example, relating belief in God to aggres- sion, which illustrates the importance of interactions. Chapter 4 has additional descrip- tion of the IRB process and problems associated with perceived unfairness. Chapter 5 has a new sample journal article and also refers to a recent list of tips for authors of journal articles. In Chapter 6 we replaced a 1952 chapter-opening example with a 2007 example, even though the author really liked the old example. In Chapter 7 the discus- sion of perceptual defense was replaced by a discussion of explicit awareness research. Chapter 8 has a new discussion of cognitive control. Chapter 9 has a new discussion of changing-criterion design as used in therapy. Chapter 10 has new examples of flash- bulb memory and the savings method. Chapter 11 now includes mention of recent neuroimaging research. Chapter 12 also adds current work on brain imaging as well as recent work on motivation and intellectual performance. Chapter 13 includes new re- search on social contagion of memory, obedience, and implicit attitudes and behavior. Chapter 14 adds new work that challenges the classical animal model of crowding and also research that improves a measure of density in a train car. Chapter 15 adds a new study on dynamic visual acuity and a brief discussion on the use of models to explain mental workload. Please continue to let the authors know how you and your students react to these substantial changes. ▼ ACKNOWLEDGMENTS It takes many more people than authors to create a text that has endured for nine editions, and the authors are pleased to acknowledge with gratitude the assistance of numerous others. Our greatest debt is to the readers of previous editions who continue to offer many useful comments. Without their helpful suggestions, this new edition would not exist. Mila Sugovic provided excellent editorial help, especially with the art work in Chapters 2, 7, and 9, and Keith Lyle and Jane McConnell provided valuable assistance in manuscript preparation and proofreading among other things, and we thank them all. We also thank Erik Evans, Rebecca Rosenberg, and Pat Waldo at Cengage and Carol O’Connell at Graphic World Publishing Services for their substantial efforts guid- ing our book through the production process. We would like to thank the following reviewers, who provided feedback to help us with this revision: Jeffrey M. Zacks, Washington University; Sandra Sego, American International College; Hallie Stephens, Southeastern Oklahoma State University; and Paul Thuras, St. Mary’s University of Minnesota. ORGANIZATION OF THE BOOK Experimental Topics 6 7 8 9 10 11 12 13 14 15 Choosing the dependent variable X Confounding X Converging operations X Counterbalancing X Demand characteristics X Ethical issues X Experimental control/ extraneous variables X X Field research X X Generalization of results X X Interaction effects X X Measurement scales X Operational definition X X Quasi-experiments X Regression artifacts X Reliability of measures X X Scale attenuation X Selection of dependent variable X X X Small-n design X X X Verbal report X X Within- and between-subjects designs X PA R T 1 FUNDAMENTALS OF RESEARCH O N E Explanation in Scientific Psychology T W O Research Techniques: Observation and Correlation T H R E E Research Techniques: Experiments F O U R Ethics in Psychological Research F I V E How to Read and Write Research Reports 1 This page intentionally left blank CHAPTER 1 EXPLANATION IN SCIENTIFIC PSYCHOLOGY MAKI NG SENSE OF THE WORLD Social Loafing Curiosity: The Wellspring of Science SOURCES OF KNOWLEDGE Fixation of Belief THE NATURE OF THE SCIENTIFIC EXPLANATION What Is a Theory? Induction and Deduction From Theory to Hypothesis Evaluating Theories Intervening Variables Foxes and Hedgehogs Roaming through Psychological Theory THE SCI ENCE OF PSYCHOLOGY Psychology and the Real World SUMMARY KEY TERM S DIS CUSSI ON QUESTIONS WEB CONNECTIONS 3  Ask any scientist what he conceives the scientific method to be, and he will adopt an expression that is at once solemn and shifty-eyed; solemn, because he feels he ought to declare an opinion, shifty-eyed because he is wondering how to conceal the fact that he has no opinion to declare. If taunted he would probably mumble something about “Induction” and “Establishing the Laws of Nature,” but if anyone working in a laboratory professed to be trying to estab- lish Laws of Nature by induction, we should begin to think he was overdue for leave. (P. B. MEDAWAR) The goal of scientific psychology is to understand why people think and act as they do. In contrast to nonscientists, who rely on informal and secondary sources of knowl- edge, psychologists use a variety of well-developed techniques to gather information and develop theoretical explanations. As one example of this scientific approach to understanding, consider the following case study of the research process. ▼ MAKING SENSE OF THE WORLD Social Loafing A common observation—one you probably have made yourself on many occasions— is that people working in a group often seem to “slack off” in their effort. Many people in groups seem willing to let a few do the work. Bibb Latané, a social psychologist, noticed this tendency and decided to study it experimentally. Initially, Latané exam- ined the research literature for evidence of this phenomenon of people working less hard in groups, which he named social loafing. One of the earliest studies of social loafing was conducted by a French agricultural engineer (Ringelmann, 1913; Kravitz & Martin, 1986) who asked people to pull on a rope as hard as they could. The subjects pulled by themselves or with one, two, or seven others. A sensitive gauge was used to measure how hard they pulled the rope. If people exert the same amount of effort in groups as when alone, then the group performance should be the sum of the efforts of all individuals. Ringelmann discovered that groups of two pulled at only 95 percent of their capacity, and groups of three and eight sank to 85 percent and 49 percent, respectively. So, it is probably not just our imaginations when we notice others (and ourselves?) seeming to put forth less effort when working in groups: Ringelmann’s research provides us with a good example of social loafing. Latané and his colleagues went on to perform a systematic series of experiments on the phenomenon of social loafing (Latané, 1981; Latané, Williams, & Harkins, 1979). They first showed that the phenomenon could be obtained in other experimental situations besides that of rope pulling. They also demonstrated that social loafing occurs in several different cultures (Gabrenya, Latané, & Wang, 1983) and even holds for young children. Thus, social loafing seems to be a pervasive characteristic of working in groups.  CHAPTER 1 EXPLANATION IN SCIENTIFIC PSYCHOLOGY 5 Latané has related this work to a more general theory of human social behavior (Latané, 1981). The evidence from the experimental studies points to diffusion of responsibility as a possible reason for social loafing. People working by themselves think they are responsible for completing the task; when they work in groups, how- ever, this feeling of responsibility diffuses to others. The same idea accounts for be- havior in other group situations: If one of your professors asks a question in a class containing only two other people, you would probably feel responsible for trying to answer. However, if there were two hundred other people in the class, you would likely feel much less responsible for answering. Similarly, people are more likely to help in an emergency when they feel the burden of responsibility than when there are several others about who could help. One possible benefit of such basic research into a phenomenon is that the findings may be applied later to solve some practical problem. A great problem in American so- ciety is the difficulty of keeping worker productivity high. Although social loafing is, at best, only one factor involved in this complicated issue, Marriott (1949) showed that fac- tory workers working in large groups produce less per individual than do those working in small groups. Thus, basic research that would show a way to overcome the problem of social loafing may be of great practical import. In fact, Williams, Harkins, and Latané (1981) found conditions that eliminated the effect of social loafing. When individual per- formance (rather than just performance of the entire group) could be monitored within the group situation, the individuals worked just as hard as they did when they worked alone. Certainly more research must be done, but it may be that simply measuring indi- vidual performance in group situations could help eliminate social loafing and increase productivity. The proposed solution may seem simple, but in many jobs only group per- formance is measured and individual performance is ignored. We have discussed Latané’s studies of social loafing as an example of psychological research to illustrate how an interesting problem can be brought into a laboratory set- ting and studied in a controlled manner. The experiments performed will, when care- fully conducted, promote a better understanding of the phenomenon of interest than will simple observation of events and reflection about them. This book is largely about the proper conduct of such experimental studies—how to develop hypotheses, arrange experimental conditions to test the hypotheses, collect observations (data) within an experiment, and then analyze and interpret the data collected. In short, in this book we try to cover the fundamentals of scientific inquiry as applied to psychology. Before examining the specifics of research, we discuss some general issues in the remainder of this chapter. The research on social loafing is used to illustrate several aspects of psychological science—its purposes, its sources, and its nature. Curiosity: The Wellspring of Science A scientist wants to discover how and why things work. In this desire, he or she is not different from a child or anyone else who is curious about the world we inhabit. The casual observer may not feel terribly frustrated if some observation (for example, that water always goes down a sink drain counterclockwise or that individual effort in a group is low) cannot be explained. However, the professional scientist has a strong desire to pursue an observation until an explanation is at hand or a problem is solved. It is not so much that scientists are more curious than other people as it is that they 6 PART 1 FUNDAMENTALS OF RESEARCH are willing to go to much greater lengths to satisfy their curiosity than are nonscien- tists. This unwillingness to tolerate unanswered questions and unsolved problems has led science to develop several techniques for obtaining relief from curiosity. It is the careful application of these techniques that distinguishes scientific curiosity from everyday curiosity. The common denominator for many of these scientific techniques is skepticism. Skepticism is the philosophical belief that the truth of all knowledge is questionable. Therefore, all inquiry must be accompanied by reasonable doubt. No scientific fact can be known with 100 percent certainty. For example, bridge engineering is a practical discipline derived from a scientific foundation in such fields as physics and metallurgy. Most people, when they drive a car across a bridge, do not actively consider that the bridge might collapse. It is a known fact that well-maintained bridges are safe. Yet in the summer of 2007, a bridge in Minneapolis–St. Paul, Minnesota, collapsed. This event will lead to further research, to result in safer bridges being built. Many of the tools, such as statistics, discussed in this text allow the skeptical scientist to measure reason- able doubt. Of what use is scientific curiosity? What purpose does it serve? We have stated that psychologists try to determine why people think and act as they do. Let us explore what this means in more detail. ▼ SOURCES OF KNOWLEDGE Fixation of Belief The scientific method is a valid way to acquire knowledge about the world around us. What characteristics of the scientific approach make it a desirable way to learn about and arrive at beliefs about the nature of things? Perhaps the best way to answer this question is to contrast science with other modes of fixing belief, since science is only one way in which beliefs are formed. More than one hundred years ago, the American philosopher Charles Sanders Peirce (1877) compared the scientific way of knowing with three other methods of developing beliefs. He called these the authority, tenacity, and a priori methods. According to Peirce, the simplest way of fixing belief is to take someone else’s word on faith. A trusted authority tells you what is true and what is false. Young children believe what their parents tell them simply because Mommy and Daddy are always right. As children get older, they may discover, unhappily, that Mom and Dad are not always correct when it comes to astrophysics, macroeconomics, computer technology, and other specialized fields of knowledge. Although this may cause children to doubt some of their parents’ earlier proclamations, it may not result in utter rejection of this method of fixing belief. Instead, some other authority may be sought. Religious beliefs are formed by the method of authority. Long after Catholic children have rejected their parents as the source of all knowledge, particularly about religious doctrine, they may still believe that the pope is infallible. Believing the news you see on television means that you accept CNN or some other news network as an authority. You may believe your professors because they are authorities. Since people lack the resources to investigate everything they learn, much knowledge and many beliefs are fixed by the method of authority. Provided nothing happens to raise doubts about the  CHAPTER 1 EXPLANATION IN SCIENTIFIC PSYCHOLOGY 7 competence of the authority setting the beliefs, this method offers the great advantages of minimum effort and substantial security. It is most pleasant in a troubled world to have complete faith in beliefs handed down to you. Another method of fixing belief is one in which a person steadfastly refuses to alter acquired knowledge, regardless of evidence to the contrary. The method of tenacity, as it was termed by Peirce, is commonly seen in racial bigots who rigidly cling to a stereotype even in the presence of a good counterexample. Although this method of maintaining a belief may not be entirely rational, we cannot say it is completely with- out value. The method of tenacity allows people to maintain a uniform and constant outlook on things, so it may relieve them from a certain amount of stress and psycho- logical discomfort. The third nonscientific method discussed by Peirce fixes belief a priori. In this context, the term a priori refers to something that is believed without prior study or examination. Propositions that seem reasonable are believed. This is an extension of the method of authority. However, there is no one particular authority being followed blindly in this method. The general cultural outlook is what seems to fix belief a priori. People once believed the world was flat, and it did seem reasonable to suppose that the sun revolved around the earth as does the moon. Indeed, the world does look flat if you are not in a spacecraft. The tenacity and a priori methods are similar in that they minimize the possibility of being influenced by conflicting opinion. In the method of tenacity, other points of view, although noticed, are completely discounted. Thus, a racial stereotype is pre- served despite other evidence, such as the good qualities of a person of a different race who lives next door. In the a priori method, other points of view go unnoticed. For example, the sight of a ship disappearing from bottom to top, instead of all at once, as it leaves port may seem irrelevant if you already know the world is flat. The last of Peirce’s methods, the scientific method, fixes belief on the basis of experience. Science is based on the assumption that events have causes and that we can discover those causes through controlled observation. This belief, that observable causes determine events, is known as determinism. If we define scientific psychology (as well as science in general) as a repeatable, self-correcting undertaking that seeks to understand phenomena on the basis of empirical observation, then we can see several advantages to the scientific method over the methods just outlined. Let us see what we mean by empirical and self-correcting and examine the advantages associated with those aspects of science. The first advantage of the scientific method is its emphasis on empirical observation. None of those other methods relies on data (observations of the world) obtained by sys- tematic observation. In other words, there is no empirical basis for fixing belief. The word empirical is derived from an old Greek word meaning “experience.” Having an empirical basis for beliefs means that experience rather than faith is the source of knowledge. Hav- ing one’s beliefs fixed by authority carries no guarantee that the authority obtained data before forming an opinion. By definition, the method of tenacity refuses to consider data, as does the a priori method. Facts that are considered in these other modes of fixing be- lief are not ordinarily obtained by systematic procedures. For example, casual observation was the “method” that led to the ideas that the world was flat and that frogs spontaneously generated from the mud each spring, as Aristotle believed. The second advantage of science is that it offers procedures for establishing the superiority of one belief over another. Persons holding different beliefs will find it difficult 8 PART 1 FUNDAMENTALS OF RESEARCH to reconcile their opinions. Science overcomes this problem. In principle, anyone can make an empirical observation, which means that scientific data can be public and can be repeatedly obtained. Through public observations, new beliefs are compared with old beliefs, and old beliefs are discarded if they do not fit the empirical facts. This does not imply that each and every scientist instantaneously drops outmoded beliefs in favor of new opinions. Changing scientific beliefs is usually a slow process, but eventually in- correct ideas are weeded out. Empirical, public observations are the cornerstone of the scientific method, because they make science a self-correcting endeavor. ▼ THE NATURE OF THE SCIENTIFIC EXPLANATION What Is a Theory? A theory can be crudely defined as a set of related statements that explains a variety of occurrences. The more the occurrences and the fewer the statements, the better the theory. The law of gravity explains falling apples, the behavior of roller coasters, and the position of bodies within the solar system. With a small number of statements about the mutual attraction of bodies, it explains a large number of events. It is therefore a powerful theory. (This does not necessarily mean it is a correct theory, since there are some events it cannot explain.) Theory in psychology performs two major functions. First, it provides a framework for the systematic and orderly display of data—that is, it serves as a convenient way for the scientist to organize data. Even the most dedicated inductive scientist will eventu- ally have difficulty remembering the outcomes of dozens of experiments. Theory can be used as a kind of filing system to help experimenters organize results. Second, it allows the scientist to generate predictions for situations in which no data have been obtained. The greater the degree of precision of these predictions, the better the theory. With the best of intentions, scientists who claim to be testing the same theory often derive from the theory different predictions about the same situation. This unfortunate circumstance is relatively more common in psychology, where many theories are stated in a loose verbal fashion, than in physics, where theories are more formal and better quantified through the use of mathematics. Although psychologists are rapidly becom- ing equipped to state their theories more precisely through such formal mechanisms as mathematics and computer simulations, the typical psychological theory is still not as precise as theories in more established, older sciences. Let us see how the theory devised by Latané to account for social loafing stacks up with regard to organization and prediction. The theory of diffusion of responsibil- ity organizes a substantial amount of data about social loafing. More important, the theory seems to account for a remarkable variety of other observations. For example, Latané (1981) notes that the size of a tip left at a restaurant table is inversely related to the number of people in the dinner party. Likewise, proportionately more people committed themselves to Christ at smaller Billy Graham crusades than at larger ones. Finally, work by Latané and Darley (1970), which is discussed in detail later in this book, shows that the willingness of people to help in a crisis is inversely related to the number of other bystanders present. The entire pattern of results can be subsumed un- der the notion of diffusion of responsibility, which asserts that people feel less respon- sibility for their own actions when they are in a group than when they are alone—so  CHAPTER 1 EXPLANATION IN SCIENTIFIC PSYCHOLOGY 9 they are less likely to help in an emergency, they are less likely to leave a large tip, and so on. Latané’s theory also makes rather precise predictions about the impact of the presence of other people on a person’s actions. In fact, one version of the theory (Latané, 1981) presents its major assumptions in terms of mathematical equations. Theories are devised to organize concepts and facts into a coherent pattern and to predict additional observations. Sometimes the two functions of theory—organization and prediction—are called description and explanation, respectively. Unfortunately, for- mulating the roles of theory in this manner often leads to an argument about the relative superiority of deductive or inductive approaches to science—a discussion the following section concludes is fruitless. According to the deductive scientist, the inductive scientist is concerned only with description. The inductive scientist defends against this charge by retorting that description is explanation—if a psychologist could correctly predict and con- trol all behavior by referring to properly organized sets of results, then that psychologist would also be explaining behavior. The argument is futile because both views are correct. If all the necessary data were properly organized, predictions could be made without recourse to a formal body of theoretical statements. Since all the data are not properly or- ganized as yet, and perhaps never will be, theories are required to bridge the gap between knowledge and ignorance. Remember, however, that theories will never be complete, because all the data will never be available. So, we have merely recast the argument be- tween inductive and deductive views about which approach will more quickly and surely lead to truth. Ultimately, description and explanation may be equivalent. The two terms describe the path taken more than they describe the eventual theoretical outcome. To avoid this pitfall, we shall refer to the two major functions of theory as organization and prediction rather than as description and explanation. Induction and Deduction Certain basic elements are shared by all approaches to science. The most important of these are data (empirical observations) and theory (organization of concepts that permit prediction of data). Science needs and uses both data and theory, and our outline of re- search on social loafing indicates that they can be interlinked in a complex way. However, in the history of science, individual scientists have differed about which is more important and which comes first. Trying to decide this is a little like trying to decide whether the chicken or the egg comes first. Science attempts to understand why things work the way they do, and, as we will argue, understanding involves both data and theory. Although Bacon recognized the importance of both data and theory, he believed in the primacy of empirical observations; modern scientists also emphasize data and view progress in science as working from data to theory. Such an approach is an example of induction, in which reasoning proceeds from particular data to a general theory. The converse approach, which emphasizes theory predicting data, is called deduction; here, reasoning proceeds from a general theory to particular data (Figure 1.1). Because many scientists and philosophers of science have argued for the primacy of one form of reasoning over the other, we will examine induction and deduction in some detail. Because empirical observations distinguish science from other modes of fixing belief, many have argued that induction must be the way that science should work. As Harré (1983) states it, “observations and the results of experiments are said to be ‘data,’ which provide a sound and solid base for the erection of the fragile edifice of scientific thought” 10 PART 1 FUNDAMENTALS OF RESEARCH THEORY Induction Deduction DATA ▼ FIGURE 1.1 A Theory Organizes and Predicts Data. By means of deduction, particular observations (data) may be predicted. By means of induction, the data suggest organizing principles (theo- ries). This circular relationship indicates that theories are tentative pictures of how data are organized. (p. 6). In the case of social loafing, the argument would be that the facts of social loafing derived from experimentation produced the theory of diffusion of responsibility. One problem with a purely inductive approach has to do with the finality of empirical observations. Scientific observations are tied to the circumstances under which they are made, which means that the laws or theories that are induced from them must also be limited in scope. Subsequent experiments in different contexts may suggest another theory or modifications to an existing one, so our theories that are induced on the basis of particular observations can (and usually do) change when other observations are made. This, of course, is a problem only if one takes an authoritarian view of ideas and believes in clinging tenaciously to a particular theory. Thus, theories induced from observations are tentative ideas, not final truths, and the theoretical changes that occur as a result of continued empirical work exemplify the self-correcting nature of science. According to the deductive view, which emphasizes the primacy of theory, the important scientific aspect of the social loafing research is the empirical guidance pro- vided by the formal theory of social loafing. Furthermore, the more general theory, diffusion of responsibility, provides an understanding of social loafing. The deductive approach holds well-developed theories in high regard. Casual observations, informal theories, and data take second place to broad theories that describe and predict a substantial number of observations. From the standpoint of the deductive approach, scientific understanding means, in part, that a theory will predict that certain kinds of empirical observations should oc- cur. In the case of social loafing, the theory of diffusion of responsibility suggests that monitoring individual performance in a group should reduce the diffusion of respon- sibility, which in turn will reduce the amount of social loafing that is observed. This prediction, as we have seen, proves to be correct. But what do correct predictions reveal? If a theory is verified by the results of experiments, a deductive scientist might have increased confidence in the veracity of the theory. However, since empirical observations are not final and can change, something other than verification may be essential for acceptance or rejection of a theory. Popper  CHAPTER 1 EXPLANATION IN SCIENTIFIC PSYCHOLOGY 11 (1961), a philosopher of science, has suggested that good theories must be fallible; that is, the empirical predictions must be capable of tests that could show them to be false. This suggestion of Popper’s has been called the falsifiability view. According to the falsifiability view, the temporary nature of induction makes negative evidence more im- portant than positive support. If a prediction is supported by data, one cannot say that the theory is true. However, if a theory leads to a prediction that is not supported by the data, then Popper would argue that the theory must be false, and it should be rejected. According to Popper, a theory can never be proven; it can only be disproven. Popper’s view about the difficulty of proving a theory can be illustrated by think- ing about a specific theory; for example, does a bag of marbles contain only black marbles? One good way to test this theory would be to reach into the bag and draw out a marble. The marble is black. What can you conclude about the theory that all the marbles are black? While the datum (one black marble) is consistent with the theory, it does not prove it. There might still be a white marble inside the bag. So pull out another marble; indeed, pull out ten more marbles. All ten are black. Is the theory now proved? No, there still might be a single white marble lurking in the bag. You would have to remove every marble to ensure that there were no white marbles. It is easy to prove the theory wrong if a white marble gets drawn. Proving the theory to be correct depends on the size of the bag. If the bag is infinitely large, the theory can never be proven because the next marble you examine might be white. Proctor and Capaldi (2001) have noted two kinds of objections to Popper’s ap- proach. First, there is a logical problem (Salmon, 1988). Since a theory potentially can always be disconfirmed by the next experiment, the number of accomplished experi- ments consistent with the theory is irrelevant. So logically a well-collaborated theory is not more valuable and does not necessarily make better predictions than a theory that has never been tested. This logical view conflicts with the practical view that scientists tend to be more comfortable with theories that have passed several experimental tests. This practical view (Kuhn, 1970) is what Proctor and Capaldi (2001) offer as the sec- ond, empirical, objection to falsification: Theories tend to be accepted, at least initially, on the basis of their ability to explain (organize) existing phenomena more than on their ability to predict new results. One problem with the deductive approach has to do with the theories themselves. Most theories include many assumptions about the world that are difficult to test and that may be wrong. In Latané’s work, one assumption underlying the general theory is that measuring a person’s behavior in an experimental context does not change the behav- ior in question. Although this often is a reasonable assumption, we will show later that people can react to being observed in unusual ways, which means that this assumption is sometimes wrong. If the untested assumptions are wrong, then a particular experiment that falsifies a theory may have falsified it for the wrong reasons. That is, the test of the theory may not have been fair or appropriate. It can be concluded, therefore, that the deductive approach by itself cannot lead to scientific understanding. At this point, you may be wondering whether scientific understanding is possible if both induction and deduction are not infallible. Do not despair. Science is self-correcting, and it can provide answers to problems, however temporary those answers may be. Sci- entific understanding changes as scientists ply their trade. We have a better understand- ing of social loafing now than we did before Latané and his coworkers undertook their research. Through a combination of induction and deduction (see Figure 1.1), science progresses toward a more thorough understanding of its problems. 12 PART 1 FUNDAMENTALS OF RESEARCH By way of concluding this section, we reexamine social loafing. Initially, positive experimental results bolstered our confidence in the general notion of social loafing. These results, in turn, suggested hypotheses about the nature of social loafing. Is it a general phenomenon that would influence even group-oriented individuals? Does it occur in the workplace as well as the laboratory? Positive answers to these questions are consistent with a diffusion-of-responsibility interpretation of social loafing. In the next phase of the research, Latané and his colleagues attempted to eliminate other explanations of social loafing by falsifying predictions made by these alternative theories. In their earlier work, Latané and his colleagues tested a particular person’s effort both when alone and when in a group. They subsequently reasoned that under these con- ditions, a person might rest during the group test so that greater effort could be allocated to the task when he or she was tested alone. To eliminate the possibility that allocation of effort rather than diffusion of responsibility accounted for social loafing, they conducted additional experiments in which a person was tested either alone or in a group—but not in both situations. Contrary to the allocation-of-effort hypothesis, the results indicated that social loafing occurred when a person was tested in just that one condition of being in a group (Harkins, Latané, & Williams, 1980). Therefore, it was concluded that diffusion of re- sponsibility was a more appropriate account of social loafing than was allocation of effort. Note the course of events here. Successive experiments pitted two possible out- comes against each other with the hope that one possibility would be eliminated and one supported by the outcome of the research. Of course, subsequent tests of the diffusion-of-responsibility theory probably will contradict it or add to it in some way. Thus, the theory might be revised or, with enough contradictions, rejected for an al- ternative explanation, itself supported by empirical observations. In any event, where we stand now is that we have constructed a reasonable view of what social loafing entails and what seems to cause it. It is the mixture of hypotheses induced from data and experimental tests deduced from theory that resulted in the theory that diffusion of responsibility leads to social loafing. From Theory to Hypothesis Theories cannot be tested directly. There is no single magical experiment that will prove a theory to be correct or incorrect. Instead, scientists perform experiments to test hypotheses that are derived from a theory. But exactly what are scientific hypotheses and where do they come from? It is important to distinguish between hypotheses and generalizations (Kluger & Tikochinsky, 2001). A hypothesis is a very specific testable statement that can be evaluated from observable data. For example, we might hypothesize that drivers older than sixty-five years would have a higher frequency of accidents involving left turns across oncoming traffic when driving at night than do younger drivers. By looking at police records of accident data, we could determine, with the help of some statistics (see Appendix B), if this hypothesis is incorrect. A generalization is a broader state- ment that cannot be tested directly. For example, we might generalize that older drivers are unsafe at any speed and should have restrictions, such as not being able to drive at night, on their driver’s license. Since “unsafe at any speed” is not clearly defined, this is not a testable statement. Similarly, the generalization does not define an age range for older drivers. However, it can be used to derive several testable hypotheses.  CHAPTER 1 EXPLANATION IN SCIENTIFIC PSYCHOLOGY 13 Figure 1.2 illustrates this process. Each generalization can produce more than one hypothesis. Only two are illustrated in the figure to keep it simple, but a good generali- zation can produce a horde of hypotheses. For example, the older-driver generalization could produce many hypotheses about different kinds of accidents and behaviors that befall aging drivers: crashing into stopped vehicles, failing to signal for turns, driving on the sidewalk, backing up into objects, not keeping within their lane, and so on. These hypotheses could be tested by making observations in traffic, on closed test tracks (safer for the driving public if the generalization is true), or in driving simulators (safest for the driving public). Now that we have explained that hypotheses come from generalizations, we can go on to the next question: Where do generalizations come from? Figure 1.2 shows there are two sources for generalizations. They can come from theory or from experience. While only three generalizations are shown in Figure 1.2, a good theory will produce a gaggle of generalizations. You may think that the aging-driver generalization comes from experience rather than from theory. You may have firsthand experience being a passenger in a car driven by a grandparent, and that experience may have caused you to agree with the generalization. This is an inductive process (see Figure 1.1) based upon data, namely casual observation of the driving behavior of elderly citizens. Hypotheses derived from this inductive process are called common-sense hypotheses. While testing common-sense hypotheses was once frowned upon in experimental psychology as be- ing inferior to testing hypotheses derived from theory, there is currently a new apprecia- tion of the value of common-sense hypotheses (Kluger & Tikochinsky, 2001). Nevertheless, most psychologists prefer testing hypotheses based upon theory. In this case, the generalization is formed deductively (see Figure 1.1) from the theory. The aging-driver generalization could also be derived from theories of attention, perception, and decision making (Kantowitz, 2001). As we age, our ability to attend to multiple tasks decreases and our decision making becomes more conservative, often requiring more time to accomplish. So an elderly driver might (a) have trouble seeing oncoming traffic at night, (b) have trouble attending to oncoming traffic while paying attention to a radio or a passenger, and (c) take a long time to decide if a left-hand turn across traffic is safe, so Theory Generalization Generalization Generalization Hypothesis Hypothesis Hypothesis Hypothesis Hypothesis Hypothesis Ev e r y d ay Ex p e rie n c e ▼ FIGURE 1.2 Gaggles of Generalizations Produce Hordes of Hypotheses. 14 PART 1 FUNDAMENTALS OF RESEARCH that when he or she finally makes the turn it is too late and oncoming traffic cannot avoid an accident. The advantage of a good theory is that it produces many generalizations. Theories of attention not only deal with aging drivers but make generalizations about many other practical situations such as operating airplanes and nuclear power plants, to say nothing of more abstract predictions to be tested in laboratories. For example, many theories of attention would predict that talking on your cell phone while you are driving would be dangerous, and indeed laboratory research suggests that it is (Steayer & Drew, 2007). However, common-sense generalizations are not productive because, even if they are correct, they do not create new generalizations. So theories are more efficient in advancing scientific inquiry. While hypothesis testing is the dominant methodology used in experimental psychology, there are other points of view. Most theories in psychology are verbal and qualitative so that mathematical predictions are hard to come by. However, if a formal model can be generated either mathematically or by computer simulation, then it becomes possible to estimate parameters of the model. Parameter estimation is superior to hypothesis testing and curve fitting (Kantowitz & Fujita, 1990), and as psychology evolves as a science, estimation will supplement, and perhaps eventually replace, hypothesis testing. Indeed, there is a new movement in the philosophy of science, called naturalism, that criticizes current methodologies such as hypothesis testing, and its tentacles have reached the shores of psychological science (Proctor & Capaldi, 2001). Naturalism suggests that methodological criteria are not fixed for eternity based on logical premises, but can change and evolve (just like theories) on pragmatic grounds. Evaluating Theories The sophisticated scientist does not try to determine if a particular theory is true or false in an absolute sense. There is no black-and-white approach to theory evaluation. A theory may be known to be incorrect in some portion and yet continue to be used. In modern physics, light is represented, according to the theory chosen, either as discrete particles called quanta or as continuous waves. Logically, light cannot be both at the same time. Thus, you might think that at least one of these two theoretical views must necessarily be false. The physicist tolerates this ambiguity (although perhaps not cheer- fully) and uses whichever representation—quantum or wave—is more appropriate. Instead of flatly stating that a theory is true, the scientist is much more likely to state that it is supported substantially by data, thereby leaving open the possibility that new data may not support the theory. Although scientists do not state that a theory is true, they must often decide which of several theories is best. As noted earlier, explanations are tentative; nevertheless, the scientist still needs to decide which theory is best for now. To do so, explicit criteria are needed for evaluating a theory. Four such criteria are parsimony, precision, testability, and ability to fit data. One important criterion was hinted at earlier when we stated that the fewer the statements in a theory, the better the theory. This criterion is called parsimony, or sometimes Occam’s razor, after William of Occam. If a theory needs a separate state- ment for every result it must explain, clearly no economy has been gained by the theory. Theories gain power when they can explain many results with few explanatory concepts. Thus, if two theories have the same number of concepts, the one that can  CHAPTER 1 EXPLANATION IN SCIENTIFIC PSYCHOLOGY 15 explain more results is a better theory. If two theories can explain the same number of results, the one with fewer explanatory concepts is preferred. Precision is another important criterion, especially in psychology (where it is often lacking). Theories that involve mathematical equations or computer problems are gen- erally more precise, and hence better, than those that use loose verbal statements (all other things being equal, of course). Unless a theory is so precise that different investi- gators can agree about its predictions, it is for all intents and purposes useless. Testability goes beyond precision. A theory can be very precise and yet not able to be tested. For example, when Einstein proposed the equivalence of matter and energy (E ⫽ mc 2), nuclear technology was not able to test this relationship directly. The scientist places a very high value on the criterion of testability, because a theory that cannot be tested can never be disproved. At first you might think this would be a good quality since it would be impossible to demonstrate that such a theory was incor- rect. The scientist takes the opposite view. For example, consider ESP (extrasensory perception). Some believers in ESP claim that the presence of a disbeliever is sufficient to prevent a person gifted with ESP from performing, because the disbeliever puts out “bad vibes” that disrupt ESP. This means that ESP cannot be evaluated, because only believers can be present when it is demonstrated. The scientist takes a dim view of this logic, and most scientists, especially psychologists, are skeptical about ESP. Belief in a theory increases as it survives tests that could reject it. Since it is logically possible that some future test may find a flaw, belief in a theory is never absolute. If it is not logically possible to test a theory, it cannot be evaluated; hence, it is useless to the scientist. If it is logically possible but not yet technically feasible, as was once the case with Einstein’s theory, then evaluation of a theory is deferred. Finally, a theory must fit the data it explains. While goodness of fit is not a suf- ficient criterion for accepting a theory (Roberts & Pashler, 2000), there is little point in pursuing a theory that fails to fit the data (Rodgers & Rowe, 2002). Intervening Variables Theories often use constructs that summarize the effects of several variables. Variables are discussed at greater length in Chapter 3. For now, we briefly describe two different kinds of variables. Independent variables are those manipulated by the experimenter. For ex- ample, not allowing rats to have any water for several hours would create an independent variable called hours of deprivation. Dependent variables are those observed by the ex- perimenter. For example, one could observe how much water a rat drinks. Science tries to explain the world by relating independent and dependent vari- ables. Intervening variables are abstract concepts that link independent variables to dependent variables. Gravity is a familiar construct that accomplishes this goal. It can relate an independent variable, the feet of height from which an object is dropped, to a dependent variable, the speed of the object when it hits the ground. Gravity also summarizes the effects of height on speed for all manner of objects. Gravity explains falling apples as well as falling baseballs. Science progresses when a single construct, such as gravity, explains outcomes in many different environments. Miller (1959) has explained how a single intervening variable, thirst, organizes experimental results efficiently. Figure 1.3 shows a direct and an indirect way to relate an independent variable, hours of deprivation, to a dependent variable, rate of bar 16 PART 1 FUNDAMENTALS OF RESEARCH Independent Variable Intervening Variable Dependent Variable Hours of deprivation Rate of bar pressing Hours of deprivation Thirst Rate of bar pressing ▼ FIGURE 1.3 One Set of Variables. pressing. The dependent variable is obtained by placing a rat into a small chamber where it can press a bar to obtain drinking water. The experimenter observes the rate (how many presses per minute) at which the rat presses the bar to get water. The direct relationship uses only one arrow to link hours of deprivation to rate of bar pressing. After doing the experiment, we could build a mathematical formula that directly relates hours of deprivation to rate of bar pressing. The indirect method