Stages in Conducting Research Research is conducted in a series of stages Each stage deals with a fundamental research issue, and each of these issues relates to the presentation of the research in the formal research report This table summarizes these relationships Research Goals and Questions Section of the Research Report Creating the research hypothesis What is the research problem? Why is the research important? What are the goals of the research? What is the relationship of this research to previous research? What is the research hypothesis? INTRODUCTION Creating the research design What research design should be used? What manipulations and/or measures should be used? What participants should be used? What procedures should be used to collect the data? METHOD Analyzing the results What statistical procedures should be used? What is a fair and accurate description of the collected data? How should the data be presented? RESULTS Interpreting the data What is the meaning of the data? What are the important conclusions of the research? What are the limitations of the research? What are the implications of the research for everyday life? What suggestions can be made for further research? DISCUSSION RESEARCH METHODS for the Behavioral Sciences FOURTH EDITION Charles Stangor University of Maryland Australia • Brazil • Japan • Korea • Mexico • Singapore • Spain • United Kingdom • United States Research Methods for the Behavioral Sciences, Fourth Edition Charles Stangor Publisher/Executive Editor: Jon-David Hague Developmental Editor: Trina Tom Editorial Assistant: Alicia McLaughlin Media Editor: Mary Noel Marketing Manager: Jessica Egbert Marketing Coordinator: Anna Andersen Marketing Communications Manager: Talis Wise Content Project Management: Pre-Press PMG © 2011, 2007 Wadsworth, Cengage Learning ALL RIGHTS RESERVED No part of this work covered by the copyright herein may be reproduced, transmitted, stored, or used in any form or by any means graphic, electronic, or mechanical, including but not limited to photocopying, recording, scanning, digitizing, taping, Web distribution, information networks, or information storage and retrieval systems, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without the prior written permission of the publisher For product information and technology assistance, contact us at Cengage Learning Customer & Sales Support, 1-800-354-9706 For permission to use material from this text or product, submit all requests online at cengage.com/permissions Further permissions questions can be emailed to permissionrequest@cengage.com Creative Director: Rob Hugel Art Director: Vernon Boes Library of Congress Control Number: 2009942928 Print Buyer: Judy Inouye ISBN-13: 978-0-8400-3197-6 Rights Acquisitions Account Manager, Text: Bob Kauser ISBN-10: 0-8400-3197-1 Rights Acquisitions Account Manager, Image: Robyn Young Wadsworth 20 Davis Drive Belmont, CA 94002-3098 USA Production Service: Pre-Press PMG Copy Editor: Pre-Press PMG Cover Designer: Irene Morris Cover Image: © Veer Compositor: Pre-Press PMG Cengage Learning is a leading provider of customized learning solutions with office locations around the globe, including Singapore, the United Kingdom, Australia, Mexico, Brazil, and Japan Locate your local office at www.cengage.com/global Cengage Learning products are represented in Canada by Nelson Education, Ltd To learn more about Wadsworth, visit www.cengage.com/Wadsworth Purchase any of our products at your local college store or at our preferred online store www.CengageBrain.com Printed in the United States of America 14 13 12 11 10 Brief Contents Preface PART ONE xv GETTING STARTED 1 Introduction to Research Developing the Research Hypothesis Ethics in Research 41 PART TWO MEASURING AND DESCRIBING PART THREE 10 PART FOUR 11 12 13 14 APPENDIX A APPENDIX B APPENDIX C APPENDIX D APPENDIX E APPENDIX F Measures 66 Reliability and Validity Surveys and Sampling Naturalistic Methods 25 65 88 106 127 TESTING RESEARCH HYPOTHESES Hypothesis Testing and Inferential Statistics Correlational Research Designs 159 Experimental Research: One-Way Designs 141 142 183 DESIGNING AND INTERPRETING RESEARCH 205 Experimental Research: Factorial Designs 206 Experimental Control and Internal Validity 227 External Validity 254 Quasi-Experimental Research Designs 272 Reporting Research Results 290 Data Preparation and Univariate Statistics Bivariate Statistics 358 Multivariate Statistics 374 Statistical Tables 395 Using Computers to Collect Data 415 Glossary 418 References 429 Index 436 338 iii Contents Preface xv PART ONE GETTING STARTED 1 Introduction to Research Behavioral Research Everyday Science Versus Empirical Research Relying on Our Intuition Discovering the Limitations of Using Intuition The Scientific Method Values Versus Facts in Scientific Research Basic and Applied Research 11 The Importance of Studying Research Methods Evaluating Research Reports 12 Conducting Research 12 Thinking Critically About Research 12 13 Research Designs: Three Approaches to Studying Behavior 13 Descriptive Research: Assessing the Current State of Affairs 14 Correlational Research: Seeking Relationships Among Variables 16 Experimental Research: Understanding the Causes of Behavior 18 The Selection of an Appropriate Method 19 Current Research in the Behavioral Sciences: Preferences for Brands That Contain the Letters of Our Own Name 20 SUMMARY 21 KEY TERMS 22 REVIEW AND DISCUSSION QUESTIONS RESEARCH PROJECT IDEAS 23 Developing the Research Hypothesis Getting Ideas 26 Solving Important Real-World Problems Using Observation and Intuition 27 Using Existing Research 28 iv 23 27 25 v CONTENTS Doing a Literature Search 30 Locating Sources of Information Conducting the Search 31 30 Formalizing Ideas Into Research Hypotheses Laws 35 Theories 35 The Research Hypothesis 37 SUMMARY 38 KEY TERMS 39 REVIEW AND DISCUSSION QUESTIONS RESEARCH PROJECT IDEAS 39 35 39 Ethics in Research 41 What Is Ethical Research? 42 Protecting Research Participants From Physical and Psychological Harm 44 Types of Threats 44 The Potential for Lasting Impact Providing Freedom of Choice 46 47 Conducting Research Outside the Laboratory 47 Securing Informed Consent 48 Weighing Informed Consent Versus the Research Goals Maintaining Awareness of Power Differentials 50 51 Avoiding Abuses of Power 51 Respecting Participants’ Privacy 51 Honestly Describing the Nature and Use of the Research When Deception Is Necessary 53 Simulation Studies: An Alternative to Deception The Consequences of Deception 54 Debriefing 54 Using Animals as Research Participants Ensuring That Research Is Ethical 57 53 56 The Institutional Review Board 59 The Researcher’s Own Ethics 60 Correctly and Honestly Reporting Research Results SUMMARY 61 KEY TERMS 61 REVIEW AND DISCUSSION QUESTIONS 62 RESEARCH PROJECT IDEAS 62 60 52 vi CONTENTS PART TWO MEASURING AND DESCRIBING 65 Measures 66 Fundamentals of Measurement Operational Definition 67 67 Converging Operations 68 Conceptual and Measured Variables Nominal and Quantitative Variables Measurement Scales 71 Self-Report Measures 69 70 72 Free-Format Self-Report Measures 72 Fixed-Format Self-Report Measures 74 Reactivity as a Limitation in Self-Report Measures Behavioral Measures 79 80 Nonreactive Measures 82 Psychophysiological Measures 82 Choosing a Measure 83 Current Research in the Behavioral Sciences: Using Multiple Measured Variables to Assess the Conceptual Variable of Panic Symptoms 84 SUMMARY 86 KEY TERMS 86 REVIEW AND DISCUSSION QUESTIONS RESEARCH PROJECT IDEAS 87 87 Reliability and Validity Random and Systematic Error Reliability 91 88 89 Test-Retest Reliability 91 Reliability as Internal Consistency Interrater Reliability 95 Construct Validity 92 95 Face Validity 96 Content Validity 97 Convergent and Discriminant Validity Criterion Validity 99 97 Improving the Reliability and Validity of Measured Variables 100 Comparing Reliability and Validity 101 Current Research in the Behavioral Sciences: The Hillyer-Joynes Kinematics Scale of Locomotion in Rats With Spinal Injuries 103 vii CONTENTS SUMMARY 104 KEY TERMS 104 REVIEW AND DISCUSSION QUESTIONS RESEARCH PROJECT IDEAS 105 105 Surveys and Sampling Surveys 106 107 Interviews 107 Questionnaires 108 Use of Existing Survey Data 109 Sampling and Generalization 110 Definition of the Population 110 Probability Sampling 110 Sampling Bias and Nonprobability Sampling Summarizing the Sample Data 112 114 Frequency Distributions 114 Descriptive Statistics 118 Sample Size and the Margin of Error 122 Current Research in the Behavioral Sciences: Assessing Americans’ Attitudes Toward Health Care SUMMARY 124 KEY TERMS 124 REVIEW AND DISCUSSION QUESTIONS RESEARCH PROJECT IDEAS 126 123 125 Naturalistic Methods 127 Naturalistic Research 128 Observational Research 129 The Unacknowledged Participant 130 The Acknowledged Participant 131 Acknowledged and Unacknowledged Observers Case Studies 132 Systematic Coding Methods 132 133 Deciding What to Observe 134 Deciding How to Record Observations Choosing Sampling Strategies 135 134 Archival Research 135 Current Research in the Behavioral Sciences: Detecting Psychopathy From Thin Slices of Behavior SUMMARY KEY TERMS 138 139 137 viii CONTENTS REVIEW AND DISCUSSION QUESTIONS RESEARCH PROJECT IDEAS 139 139 PART THREE TESTING RESEARCH HYPOTHESES 141 Hypothesis Testing and Inferential Statistics Probability and Inferential Statistics 143 Sampling Distributions and Hypothesis Testing The Null Hypothesis 146 Testing for Statistical Significance Reduction of Inferential Errors 142 145 147 149 Type Errors 149 Type Errors 150 Statistical Power 151 The Tradeoff Between Type and Type Errors Statistical Significance and the Effect Size 152 153 Practical Uses of the Effect-Size Statistic 154 SUMMARY 156 KEY TERMS 156 REVIEW AND DISCUSSION QUESTIONS 157 RESEARCH PROJECT IDEAS 157 Correlational Research Designs 159 Associations Among Quantitative Variables 160 Linear Relationships 162 Nonlinear Relationships 162 Statistical Assessment of Relationships The Pearson Correlation Coefficient The Chi-Square Statistic 164 Multiple 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setting of, 151, 152; Type error, 149, 150, 382 Alternative explanations, 231 American Psychological Association (APA): ethical principles, 43, 44 guidelines for publication, 293; research guidelines, 49; research report format, 11; website, 31, 43; table 3.1., table 3.4 Analysis of Covariance, 379 Analysis of Variance, See ANOVA Anderson, C A., 136, 271 Anderson, D B., 270 Animal research: guidelines on, 58, table 3.4; reasons for use of, 56, 57 Annual Review of Psychology, 30 ANOVA summary table: degrees of freedom, 191, 192 and figure 10.3; explanation of, 191–193, 193, 194; F statistic, 371 ANOVA: between-groups/withingroups,171, 192; in experimental designs, 190, 191; SPSS output, 371, table C.5; one-way betweenparticipants, 369–370, 371 Applebaum, M I., 283 Applied research, 11, 12 Archival research, 135 Arithmetic mean, 118; Arnold, W J., 270 Aronson, E., 58, 81, 129, 259, 270 Artifacts, 242 Ashby, F G., 245 Association, 184, 185 Associative lists, 73 See also Variables Attrition, 278 Austin, E W., 109 Automated experiments, 236 Baddeley, A D., 257 Bakeman, R., 134 436 Banaji, M R., 259 Banks, C., 54 Bar charts, 114, 114–115 fig 6.1, 145 fig 8.2, 212 Barbaree, H E., 243 Barlow, T A., 84 Baron, K S., 59 Baron, R A., 270 Baron, R M., 262 Bartholow, B D., 83 Baseline measure, 233 Basic research, 11, 12 Basso, D., 103 Baumrind, D., 53 Baxter, P M., 30 Beaman, A L., 81 Beattie, A E., 73 Beattie, M., 103 Beaubien, J M., 265 Before-after research designs, 232, 233 and fig 12.1 Behavioral measures: criterion variable, 99; nonreactive measures of, 82; psychophysiological measures of, 82, 83; reliability for, 91, 134; used in conceptual variables, 81; table 4.5 variables based on, 80 Behavioral research: animals in, 57; archival research in, 135, 136; everyday science, 4, 5, 6; explanation of, 3; goals of, 13–15; organizing principles of, 35–38; requirements of, 10; uses of, 3–5, 7, Bem, D J., 295 Berkowitz, L., 259, 283 Bernstein, I., 284 Berntson, G G., 82 Berscheid, E., 59 Bersoff, D N., Beta weights, 168, 169, See Regression coefficients Beta, 151 Between-groups variance, 191 Between-participants designs, 186 and fig 10.1 Binomial distribution, 145 fig 8.2, 145–147 Bissonnette, V., 284 Bivariate regression, 366–368 Bivariate statistics, 359 Blackman, D.,57 Blehar, M D., 136 Blind experimenters, 246, 247 Blocked random assignment, 248, and table 12.2, 247, 248 Bodenhausen, G V., 81 Boland, F J., 243 Borgida, E., Bower, G H., 46 Bramel, D., 44 Breitholtz, E., 84 Brendl, C.M 20 Bresnahan, J., 103 Brierley, B., 265 Brown, S L., 265 Brown, T A., 84 Brown vs Board of Education, Buchanan, T W., 286 Cacioppo, J T., 82, 237 Cahill, L., 268 Calculating r: computation of, 360; on the mean deviation, 359–360 Campbell, D T., 82, 229, 241, 273, 274 Canonical correlation, 387–388 Carlsmith, J M., 129, 258, 271 Carr, C., 241, 244 Carvallo, M., 20 Carryover, 195 Cartoon type, 186 Case studies, 132, 133 Caulkins, R S., 270 Cells, 207 Census, 110 Central limit theorem, 354 Central tendency: definition of, 118; calculation of, 349; measures of, 118–121, 120 fig 6.5, 121 Chaiken, S., 81 Chattopadhyay, A., 20 Chi-square statistic, 164–167 and table 9.2 Chi-square test for independence, 362–364 Chravala, C., 29 Clark, D M., 84 Clubb, J M., 109 Cluster sampling, 112 Coefficient alpha: evaluating reliability, 94; multivariate statistics, 383–384 INDEX Coefficient of determination, 164 Cohen, J., 151, 155, 378, 379, 414 Cohen, P., 378, 379 Cohen, S., 81 College students: advantages/disadvantages in using, 256–258 Column marginal frequencies, 362 Common sense, Common-causal variables, 170, 171, 172, 175, 176, 185–186, 187 Communication of scientific knowledge, 291–292 Comparison-group before-after designs, 278–279 Comparison-group designs, 276–277 Complex comparisons, 221, 222, 380 Computer software packages, 417 statistical table F.1 Computers: for data collection, 416–417; data preparation and, 339–345; for descriptive statistics, 351–352 Conceptual replications, 260, 261 Conceptual variables: correlational relationship design of, 69, 70; in correlational research design, 69 fig 4.1; explanation of, 67, 68; as latent variables, 168; in a Likert scale, 89 and 90 fig 5.1; operation definitions of, 67, 68, table 4.1; reliability analysis, 386 types of, 81 table 4.5 See also Variables Concurrent validity, 99 Condition means, 197, 198 fig 10.5, 210 fig 11.3, fig 11.6, 217, table 11.1, 219, 221 Conditions, 186, 207 Confidence intervals, 122, 355 Confirmatory factor analysis, 388–389 Confound checks, 241, 242, 246–247, 248 Confounding variables, 230, 231, 239, 240 Construct validity: assessing, 97, 98; content validity, 96 and table 5.2; explanation of, 95, 96 table 5.2; face validity, 96; in naturalistic research, 128, 129; threats to, 228, 229 and table 12.1 Constructive replications, 261, 262 Content analysis: archival records coded by, 136; coding free-response data as, 74 Content validity, 97 Contingency tables: calculating chi-square (χ2), 165 and table 9.2; chi-square test for independence, 362–364; coding of raters, 365 table C.4; SPSS output, 363 table C.3 Contrast analysis, 380 Contrast tests, 222 Contrast weights, 381–382 Contrasts, 380–382 Control conditions, 188 Convenience samples, 113, 114 Convergent validity, 97–99 Converging operations, 20, 68, 69 Cook, S W., 72 Cook, T D., 241, 274 Coombs, C H., 67 Cooper, J., 82 Correlation matrix, 166, 167 table 9.3, 167 table 9.4, 361 table C.2 Correlational data: path analysis, 174–175, 176; structural equation analysis, 176, 178 and fig 9.6 Correlational research designs: advantages/disadvantages of, 177, 178; based on research hypothesis, 37; and causality, 170–176, 177, 178; explanation of, 19, 20; patterns of association sample, 160 table 9.1; strengths and limitations of, 19, 20; variables in, 67 fig 4.1, 69, See also Research designs Correlations: coefficient, 165 fig 9.3; interpreting, 170–172, 173; SPSS output, 361 table c.2; use of, 16, 17; between variables, 184, 185 See also Pearson correlation coefficient Counterbalancing, 195, 196 Cover stories, 243, 244 Cramer’s statistic, 364 Crandall, R., 44 Criterion validity, 99–100 Criterion variable, 96, 97, 99 Critical values of chi-square, 405 statistical table E Critical values of F, 406–407 statistical table F Critical values of r, 403–404 statistical table D Critical values of t, 402 statistical table C Cronbach’s coefficient alpha, 94 Cross, T., Cross-cultural replications, 263 Crossover interaction, 215 Cross-sectional research designs, 175, 283 Crowder, R G., 259 Crowne, D P., 80 Current Contents, 31 Curvilinear relationships, 163, 189 and fig 10.2 Data: plural usage of 4, 340–341, 342 Data analysis: by computer software programs, 340–341 and fig B.1, 342; deletions from, 344–347; different approaches to, 391–392; missing data from, 343–344; preparing for, 339–346 Data: analyzing the, 339–340; anonymity and confidentiality in, 51, 52; collecting, 339; collecting by computer 437 software packages, 417 table F.1; define, 4; deleting and retaining, 344–347; entering process, 340–342; event frequencies/duration, 134, 135; free-format, 73, 74, 75; interpretation of, 6–8; 10, 11; transforming, 346; uses of, Databases, 32–35, 33 fig 2.1, 34 fig 2.2 David, A S., 265 Davis, J A., 109 Deaux, K., Debriefing, 45 table 3.1, 54–56 Deception, 45 table 3.1, 52–54 Deductive method, 35 Degrees of freedom (df), 167, 191, 192 Demand characteristics, 243–245 Demographic variables, 283 Denzin, N K., 15 Department of Health and Human Services: ethical standards guidelines website, 44; informed consent guidelines, 48; regulations on proposed research, 59, 60, 61 Dependent variables, 37, 238, 69, 184, 186, 187, 188, 242 Dermer, M., 59 Descriptive research, 14–16 See also Research designs Descriptive statistics: calculation of, 330 table B.1; checking accuracy of, 342–343; computing, 348–353; definition of, 118; explanation of, 346; measures of, 118–121, 122; SPSS output, 353 table B.2; SPSS printout of, 119 fig 6.4 Deutsch, M., 72 Dickerson, C A., 81 Diener, E., 44, 81 Dillman, D A., 109 Dillworth, D., 270 Discriminant validity, 97–99, 99 Dispersion: definition of, 118; measures of, 121, 350, 353 Disproportionate stratified sample, 112 Distracter items, 101 Distributions: binomial, 145 fig 8.2, 146; normal, 119, 120 fig 6.5; patterns and, 118; positive/negative skew, 119, 120 fig 6.5; sampling, 146 and fig 8.3; shapes of, 120 fig 6.5; types of, 119 Donnerstein, E., 259 Dougherty, D., Dowden, C., 265 Downing, L L., 270 Durkheim, E., 136 Dushenko, T W., 53 Dyer, M A., 270 Eagly, A H., 29 Ecological validity, 128, 129, 258, 259 438 INDEX Effect size, 191, 266, 364; explanation of, 151, 152; one-way ANOVA and, 371; statistical significance and the, 153–155 Effrein, E A., 81 Eisenberger, N I., 199 Ekman, P., 252 Eliott, A., 248 Ellsworth, P C., 251 Empirical statements, 4, 5, Equivalence, 18, 186, 187 Equivalent-forms reliability, 92 ERIC, 32 Ericsson, K A., 73 Eron, L D., 174 Eta, 374, See also F Ethical research: abuse of power in, 51; animals in, 57, 58; APA guidelines, 45, 45 table 3.1; basic goals of, 43, 44; characteristics of, 56 table 3.3; cost-benefit analysis of, 59, 60, 61; deception in, 52–53, 54; explanation of, 41–43, 43; informed consent, 48–52; participants’ privacy, 51, 52; protecting participants, 44–47 Event sampling, 135–136 Everyday behavior: measured variables of, 128, 129 Everyday science, 5, Exact replications, 260 Existing research, 28, 29 Expected frequencies, 363 Experimental condition, 188 Experimental control: before-after research designs, 232, 233 and fig 12.1; confounding variables, 230, 231; explanation of, 229; extraneous variables, 230, 233 fig 12.1; matched-group designs, 234, 235 Experimental manipulations, See Manipulations Experimental realism, 236, 237 Experimental research designs: advantages/disadvantages of, 198, 199; choosing an, 281–282; comparison of the condition means, 219–222; creating equivalence in, 186–187, 193; demonstrating causality, 183–184; factorial designs, 207–219; factors of, 173, 174; hypothesis testing in, 190–191; levels in, 188–189, 190; one-way, 185–192, 186 fig 10.1, 192–193, and fig 10.4, 194; repeated-measures, 193–196, 193 fig 10.4, 197; three-level, 189 and fig 10.2; two-level, 188–189, 192; two-way factorial design, 208 and fig 11.1 Experimental research: based on research hypothesis, 37; explanation of, 18; goals of, 256–257; strengths and limitations of, 19, 194–196; use of variables, 184 See also Research designs Experimental script, 236 Experimenter bias, 245, 246 Experiments: elements of, 18, 19 Experimentwise alpha, 221 External validity: explanation of, 229, 256; generalization, 256, 258; threats to, 229 table 12.1, 255–267; understanding, 255, 256 Extraneous variables: examples of, 187; explanation of, 172; limited population designs, 232; matched-group design and, 234 and fig 12.2, 235 F test, 146 F, 191, 192, 212 Face validity, 96 and table 5.2, 97 Factor analysis: exploratory, 387; rotated factor matrix, 385 table D.3 Factor loading matrix, 384–386 and table D.3, 387 Factor loadings, 396, 389 Factor scores, 387 Factor, 207 Factorial experimental designs: ANOVA summary table, 211–212 and fig 11.4, 213; interactions, 213–215, 216; line chart, 213, 214 and fig 11.5; main effects, 209–211, 214–216 and fig 11.5; schematic diagram, 209, 210 and fig 11.2; simple effects, 211; three-way, 216–217 and table 11.1, 217; two-way design, 208–210 and fig 11.2, 210 fig 11.3, 214 fig 11.5; × factorial design, 240 See also Constructive replications Factors, 386 Facts, 8–10, 11 Falender, V J., 81 Falsifiable theories, 36 Fazio, R H., 81 Festinger, L., 130 Fidell, L S., 383 Field experiments, 259 Fisher Least Significant Difference (LSD) Test, 382 Fisher, R A., 401, 402, 404, 405 Fiske, S T., 3, 6, 73 Fixed-format self-report measures, 74–77 Focus group, 108 Fode, K L., 245 Ford, T E., 73 Forsyth, D R., 59 Fowler, K P., 137 Fraser, S C., 81 Free-format self-report measures, 72, 73, 74 See also Variables Freeman, H E., 155, 273 Frequencies, 362 Frequency curve: definition of, 116; quantitative variables in, 117 fig 6.2; shapes of distributions, 120 fig 6.5 Frequency distributions: bar chart and, 116 fig 6.1; definition of, 114; grouped, 115; raw data sample, 115 table 6.1; types of, 350–351; variables in, 116 fig 6.1 Freud, S., 6, 26, 135 Friesen, W V., 252 Frey, K S., 79 Geda, C L., 109 Gelfand, H., 293 General linear model (GLM), 379–380 General Social Survey, 109 General theories, 36 Generalization: across participants, 256–258, 262–263; across settings, 258–259; explanation of, 256 Gerard, H B., 270 Gilbert, D T., 301 Glass, G V., 265, 266 Goodness of fit statistic, 389–390 Gosling, S., 81 Gosman, E J., 17 Gottman, J M., 134 Grand mean, 369–370 Greenberg, B S., 136 Greenberg, J., 81 Greenwald, A G., 65 Grouped frequency distribution: explanation of, 115, 116; histogram, 116, 117 fig.6.2; quantitative variable resulting in, 116 Grove, J B., 82 Gully, S M., 265 Gursley, D.M., 84 Guttman scale, 78–79 and table 4.4 Guttman, L., 78 H, 147 Haney, C., 54 Hangnel, S., 15 Harackiewicz, J M., 81 Hardy, D J., 265 Harmon-Jones, E., 83 Harris, R J., 383 Hastie, R., Hays, W L., 380 Heider, F., Heilman, M E., Herrnstein, R J., 10 Hertwig, R., 54 Hewstone, M., 281 Hierarchical multiple regression, 378 Hillyer, J E., 103 Hindsight bias, Hinkin, C H., 265 Histogram, 116, 117 fig 6.2, 348 History threats, 378 Holmes, D S., 252 Hsee, C K., INDEX Hubbard, M., 55 Huesman, L R., 174 Hull, J G., 46 Human Area Relations Files, 109 Humphreys, L 130 Ickes, W., 258, 284 Ideas: Internet sites, 30, 31; sources of, 26–29; strategies for developing, 28, 29, 30 Impact, 236, 237 Incalcaterra, K A., 265 Inclusion criteria, 264, 266 Independent variables, 37, 38, 162–163, 199, 242–243 Individual sampling, 135 Inductive method, 27, 28 Inferences of causality, See Experimental research Inferential statistics, 143–145, 354–356 Informed consent, 45 table 3.1, 46–51; research goals vs., 50, 51; sample form, 49 table 3.2 Institutional Review Board (IRB), 59 Interaction, 211 Intercept, 375–376 Internal analysis, 28, 239 Internal consistency: explanation of, 94; interrater reliability in, 95 Internal validity: confirmation of, 231; explanation of, 229; threats to, 229 table 12.1, 241–249, 276 table 14.1, 277–279, 284–286 See also Valid research Internet: research literature sources and the, 30–31 Interrater reliability, 95, 136, 137 Interval scale, 71, 72 Interviews, 107, 108 Intuition: limitations of, 6–8; with observational research, 27, 28; without testing, Isen, A M., 245 Items, 74 Item-to-Total Correlations, 94, 95 Jahoda, M., 72 Jetten, J., 19, 81 Johnson, R D., 270 Johnson, S., 293 Jonas, K., 281 Joshi, A., 265 Joynes, R L., 103 Kahle, L R., 46 Kappa: explanation of, 95; reliability test, 364–365 Kassin, S M., 225 Kavannagh, D J., 268 Kelem, R T., 81 Kelly, H H., Kemper, D., 270 Kenny, D A., 262 Keppel, G., 380, 383 Keyword search, 32–35 Kiechel, K L., 226 Kim, H., 81 Kimmel, A., 54 Kirschbaum, C., 286 Knight, L J., 243 Knowles, E., 284 Ko, S., 81 Koehler, K A., 84 Kohlberg, L., 36 Langer, E J., 251 Latent variables, 177, 389 See also Conceptual variables Latin square designs, 196 Laws, 35 Lefkowitz, M M., 174 Leippe, M R., Lepper, M R., 55 Levels, 186, 188, 189, 207 Levin, P F., 245 Levine, D., 270 Lewin, K., 12 Libman, M., 59 Lieberman, J., 81 Lieberman, M D., 199 Likert scale: explanation of, 75, 77; reverse-scored on, 346; Rosenberg self-esteem scale, 75 and table 4.2 Likert, R., 75 Lilenfeld, S O., 137 Limiting conditions, 28, 29 Lincoln, Y S., 15 Lindsay, R C L., 53 Linear relationships, 162 Linton, P., 293 Literature search, 30–35 Litowitz, D L., 270 Loglinear analysis, 379–380 Longitudinal research designs: conducting, 173–174, 175; limitation of, 175; time-series designs, 281–282 and fig 14.2, 283 Lord, C G., 301 Lytle, B., 179 Macaulay, J., 283 Macrae, C N., 19, 81, 244 Madey, S F., 270 Madigan, R., 293 Main effects, 209–210, 239 Manderlink, G., 81 Manipulated, 186 Manipulation checks, 237–238, 239 Manipulations, 18, 37, 60, 186–189, 190, 236–241, 241, 242 Mann, C., 266 Mannarelli, T., 81 MANOVA, 387–388 Margin of error, 122 Marginal means, 210 439 Markus, H., 81, 225 Marlow, D., 80 Marsden, P., 109 Matched-group designs, 234, 235 Mathews, A.M., 84 Matthewson, G C., 270 Maturation threats, 298 McCall, R B., 283 McCann, I L., 252 McGhee, D E., 85 McGregor, H., 81 McGuire, W., 27 McNally, R J., 84 Mean deviation scores, 219–221, 380–381, 382 Mean deviation, 121 Means comparisons, 219–221, 380–381, 382 Means, 118, 388–389 Measured variables: correlational research design of, 69 and fig 4.1, 70; creating valid, 100–102; descriptive statistics of, 118; distribution, 119; effectiveness of, 89–99, 100; everyday behavior, 128, 129; explanation of, 67, 69 fig 4.1; with regression to the mean, 279–280, 281; systematic observation, 184; types of, 70, 71, 82, 83; types of behavioral variables of, 81, 81 See also Variables Measurement, 67 Measures: choosing, 83, 84 See also Variables Median, 119, 349–350 Mediating variables, 172, 173 Mediator, 172 Medline, 32 Merles, I M., 84 Meta-analysis, 264–265 table 13.1, 266 Milberg, S J., 73 Milgram, S., 44, 46, 237 Mill, J S., 184 Miller, D T., 245 Miller, D., 81 Miller, N E., 57 Miller, R L., 265, 266 Mills, J., 55, 58, 237, 270 Milne, A B., 18, 51 Mitchell, G., 248 Mixed factorial designs, 218–219 fig 11.6, 220 Mode, 118, 119, 120, 349–350 Moderator variables, 262 Modin, B., 136 Money, R., 84 Morgan, C D., 73 Mori, D., 81 Morris, K J., 237 Morris, M., 81 Mortality, 278 Multi-modal, 349–350 Multiple correlation coefficient (R), 168, 378 440 INDEX Multiple regression: analysis output from a, 377 table D.1; ANOVA and, 379, 380; explanation of, 168; goal of, 375–376; independent variables measured, 169 fig 9.4; testing mediators, 172 Multivariate Analysis of Variance, See MANOVA Multivariate F, 387–388 Multivariate statistics, 383–384 Mundane realism, 269 Murray, C., 10 Murray, H A., 73 Naive experimenters, 246 Narrative research reviews, 266–267 Naturalistic observation: descriptive research as, 14 Naturalistic research, 128, 129, 136 table 7.1 Nettles, M T., 17 Neuberg, S L., 73 Niesta, D., 248 Nisbett, R E., 5, Nolen-Hoeksema, S., 265 Nominal variables: chi-square statistic, 165, 166; explanation of, 70; kappa, 95 See also Variables Nonlinear relationships, 162, 163, 189, 190 Nonmological net, 99 Nonprobability samples, 112, 113, 114 Nonreactive measures, 82, 244–245 Normal distribution, 352–353 and fig B.2 See also Distributions Null hypothesis: nonrejection of, 146 fig 8.4; rejecting the, 147, 150 and fig 8.4; statistically significant/nonsignificant, 148; testing by, 146–147; Type and Type errors, 149–151, 150 fig 8.4, 151 Nygren, T D., 245 Nunnally, J C , 70 Objective procedures, Observational research: coding sheet sample, 131 fig 7.1; explanation of, 129; participant/ observer in, 129, 130; participation and acknowledgment, 131 table 7.1; systematic coding methods, 148; types of, 128–129, 132; use of inductive method, 27, 28 Observed frequencies, 362 Observed means patterns, 213–214, 215 Observers: acknowledge/unacknowledged, 130–132 O’Connor, P J., 136 One-shot case studies, 274 One-way experimental designs, 185–196, 192–193 and fig 10.4 See also Experimental research designs Operational definitions, 67, 68 table 4.1; conceptual variables and, 68 table 4.1, 69 See also Variables Ordinal scale, 71, 72 Ortmann, C E., 54 Osgood, C E., 77 Osk, I G., 84 Ostrom, T M., Outcome variables, 37, 38, 169 and fig 9.4, 170–174, 175 Outliers, 119, 120 fig 6.5, 345 Oversampling, 112 Pairwise comparison, 219–221 Panel study, See Longitudinal research designs Parameter, 346–347, 354; Parsimonious theories, 36; Participant replications, 262–263 Parr, J M., 268 Participant variable, 283; Participants: confidentiality of, 42, 52; educational value for, 55; freedom of choice, 47–50, 51; informed consent, 48–50, 51; psychological impact on, 46, 47 Participant-variable design, 283–284 Path analysis, 174–175 Path diagram, 174 and fig 9.5 Patrick, C J., 137 Pearson correlation coefficient: statistical assessment by, 163, 164 Pearson product-moment correlation coefficient: calculating r, 359–361 and table C.1; explanation of, 16; influences of errors, 90, 91; predictor variable, 17, 18 table 1.2; samplings distributions, 146 Pearson’s r, See Calculating r Peer review, 294–295 Pennebaker, J W., 290 Percentile rank, 353 Personality variables, 284 Peterson, R A., 84 Petty, R E., 237 Pham, M T., 222 Phi, 364 Piaget, J., 26, 36, 132 Piliavin, I M., 47 Piliavin, J A., 47 Pilot testing, 100, 240, 241 Placebo effects, 242, 243 Planned comparisons, 221 Pliner, P., 81 Plous, S., 57 Pomerantz, E M., 131, 134–135 Popper, K R., 36 Population, 110, 112, 113 Post hoc comparisons, 221 Post hoc means comparisons, 382–383 Postexperimental interviews, 55, 226, 227 Pratfall, Predictions: as main effects, 215; as research hypothesis, 37, 38; use of correlations, 16, 17 Predictive validity, 99 Predictor variables: common-causal variables, 171; independent variables, 37–38; multiple regression, 163; in regression analysis, 168–169 and fig 9.4; in relation to outcome variables, 172–173, 174; in scatterplots, 163 Prentice, D A., 245 Presser, S., 109 Price, L., 242 Primary sources: computer databases, 32, 44; Internet sites and, 30, 31; research reports, 30, 31 Priori comparisons, 221 Probability analysis, 145, 146 Probability sampling, 110, 112, 113 Probability statistics, 143–144, 145 Probability values, See p-values Process debriefing, 54 Program evaluation research, 11, 273–274 Projective measure, 73 Proportion of agreement, 365 Proportion of explained variability, 155 Proportionate stratified sample, 111, 112 Protocol, 236 Provisional idea theories, 35, 36 Psychological Bulletin, 30 Psychophysiological measures, 82, 83 PsycINFO, 32 p-values: calculating, 346; comparing to Alpha, 144 fig 8,1, 147, 148; obtaining, 361, 362; two-sided, 148, 149 Qualitative data, 128, 133, 134 Qualitative research, 14, 15, 132 Quantitative data, 128 Quantitative research, 14, 15 Quantitative variables: correlation coefficient, 164; explanation of, 70, 71; patterns of association, 162 and fig 9.2, 169 See also Variables Quasi-experimental research designs: comparison-group, 276–277; comparison-group-before-after design, 278–279; explanation of, 274; participant-variable design, 283, 284; single-group before-after design, 277, 278; single-group design, 274, 275 and fig 14.1, 258; singleparticipant designs, 284–286, and fig 14.3; summary of, fig 14.1; threats to validity, 276 table 14.1 Questionnaires: advantages and disadvantages of, 109–109; mailed, 113 See also Fixed-format self-report measures INDEX Random assignment to conditions, 186 fig 10.1, 187, 208 and fig 11.1, 209, 247–248 and table 12.2, 396 Random error: explanation of, 89, measured variable by, 90 and fig 5.1; measurement with, 143–144; self-canceling by, 89, 90 Random numbers, 396 Random sample, 396 Random sampling, 111 Range, 121, 350 Ransberger, V M., 270 Ratio scales, 71, 72 Raw data, 114, 115 Reactivity, 79, 80 Reciprocal causation, 170 Reed, J G., 30 Regression coefficients: explanation of, 257; independent variables, 356; relationship of predictor variables, 168, 169 fig 9.4, 170 Regression equation, 366, 367 fig C.1 Regression line, 161, 367, 369 Regression to the mean, 279–281 Reiss, S., 84 Reliability analysis, 383, 384 table D.2 Reliability: approaches to assessing, 81 table 5.1; basis of, 93, 94; code analysis, 134–135; comparing validity and, 101–102; explanation of, 91; internal consistency of, 94; testretest procedures in, 92 Repeated-measures designs: advantages/ disadvantages of, 194–195, 196–197; explanation of, 186; in factorial research, 218–219 fig 11.6, 220; oneway, 195 fig.10.4; reversal design, 285; when to use, 196–187 Replications: explanation of, 8, 260, 261; types of, 261–263 Representative sample, 119 Research designs: approaches to, 13, 14; characteristics of, 20 table 1.3; recognizing and controlling variables in, 231–235, 236; selection of, 19–20; types of, 19–20 Research hypothesis: explanation of, 37; explanatory measurement of, 37; formalizing ideas, 35–36; 37–38; hypothesis-testing flow chart, 144 fig 8.1; hypothesis testing procedure, 149, 150 and fig 8.4; testing the, 70; use of variables and, 70 Research participants: types of threats to, 44–46 Research programs: interpreting research literature, 267; need for, 263–264; results of, 264–267 Research reports: abstract of, 299–301; APA format, 294, 298–299, 310; APA format checklist, 297 table A.1, 308– 309 fig A.1; APA reference format, 308–309 fig A.2; conducting, 12, 13; critical thinking and, 12; discussion of, 306–307, 309; evaluating, 12; explanation of, 10–11; footnotes and author notes of, 309; honesty in, 59–61; “hourglass shape,” 298 fig A.1; introduction of, 302–303, 304; method, 303–304; presentation of results in, 197–198, 199, and fig 10.5; references of, 304; results of, 304–305; sample of, 314–337; samplings procedures in, 114; sections of, 295–296; tables and figures of, 309; tips on writing, 310–311; title page of the, 299 Research results: reporting, 299–309, 310; in scientific journals, 292–294, 295 Research: choosing a measure, 93, 94; communicating scientific knowledge, 291–309, 310; informed consent vs goals, 50–51; professional collaboration, 201; publication process, 292–294, 295; understanding methods of, 12, 13 Researchers: communication between, 291–292 Response rate, 109, 113 Restriction of range, 164, 165 fig 9.3 Retesting effects, 92, 278 Reversal design, 285 Reverse causation, 170–171 See also Longitudinal research designs Review papers, 264 Richardson, D., 55 Riecken, H W., 130 Robinson, J P., 102 Rodin, J., 47 Rokeach, M., 133 Rosenberg self-esteem scale, 75 and table 4.2, 76–77, 93, 94, 96, 284 table D.2 Rosenberg, M., 75 Rosenhan, D L., 130 Rosenthal, R., 43, 153, 245, 266, 380 Rosnow, R L., 153, 380 Ross, L., 5, 55 Rossi, P H., 155, 273 Rounding, 348 Row marginal frequencies, 362 Roy, D F., 129, 131 Rubin, Z., 53 Ruble, D N., 36 Running head, 299 Sample size, 155–156, 167 Sample, 110 Sampling distribution of the mean, 354–355 Sampling frame, 111, 113 Sampling: bias, 112–113; definition of, 110; distribution, 146 and fig 8.3; 441 distribution of the mean, 334, 335; probability, 122; proportionate and disproportionate, 111–112; types of, 110–113; types of strategies, 135 Sansone, C., 81 Saxe, L., Scales: advantage of fixed-format, 74; explanation of, 71, 74; fixed-format self-report measure, 74; Likert, 75–77; of measurement, 72–73 Scaling, 69 Scatterplot, 161, 367 fig C.1 Schachter, S., 130 Scheffé Means Comparison Test, 382 Scherer, K R., 252 Schlenker, B R., 59 Schmitt, D P., 265 Schuman, H., 109 Schwartz, J L K., 85 Schwartz, R D., 82 Schwarz, N., 109 Scientific fraud, 60–63 Scientific knowledge: accumulation of, 6, 37; communication of, 291–292 Scientific method, Scientific notation, 351 Scientific research reports, 10–12 Scientific research: ethics in, 42–44; values vs facts, 8–10, table 1.1, 11 Sears, D O., 232, 258 Sechrest, L., 92 Secondary sources, 30–31 Selection threats, 277 Self-monitoring scale, 97–99 Self-promotion, 79–80 Self-report measures: fixed-format, 74–78, 79; free-format, 72–74 See also Variables Selltiz, C., 72 Semantic differential, 79 and table 4.3 Shaver, P R., 102 Shaw, P., 265 Shear, D M., 84 Sherer, K R., 252 Sholomskas, D E., 84 Shrout, P E., 147 Sigall, H., 237 Sigelman, J., 83 Significance level, See Alpha Simo, M., 270 Simon, H A., 73 Simonton, D K., 137 Simple effect, 211 Simple random sampling, 111 Simulation studies, 53–54 Simultaneous multiple regression, 378 Single-group before-after design, 277–278 Single-group design, 274–276, 275 fig 14.1, 276 table 14.1 Single-participant designs, 284–295 and fig 14.3, 285 442 INDEX Skewed, 119 Skika, L., 179 Slaby, R G., 78, 79 Smith, A P., 81 Smith, M L., 265 266 Smith, S S., 54, 55 Smith, T W., 109 Snowball sampling, 113 Snyder, M., 98 Social desirability, 79 Social Science Citation Index (SSCI), 32 Society for Research in Child Development (SRCD), 49 Solomon, S., 81 Sperry, R W., 133 Split-half reliability, 94 SPSS, 166, 167 table 9.3, 340, 341 fig B.1 Spurious relationship, 171–172 Standard deviation, 118, 121, 350, 354 Standard error of the mean, 354–355 Standard normal distribution, 353 fig B.2, 298–399 statistical table B Standard score, 352 Standardization of conditions, 235–236 Standardized regression coefficients, 376 See also Regression coefficients Stangor, C., 36, 73, 241, 244, 281 Stanley, J C., 229, 241, 274 States, 93 See also Conceptual variables Statistical analysis: choosing the, 391–392 and fig D.2; conducting, 346–347 Statistical conclusion validity: threats to, 228, 229 table 12.1 Statistical notation, 347–348 Statistical Package for the Social Sciences, See SPSS Statistical power, 151–152, 414 statistical table G Statistical procedures: analysis of covariance, 379; Analysis of Variance (ANOVA), 190–192, 193; canonical correlation, 387–388; guide to the use of, 339–356; inferential statistics, 145; meta-analysis, 264–267 and table 13.1; multiple regression, 375– 376; structural equation analysis, 175, 177 and fig 9.6, 178; univariate statistics, 383 Statistical significance: effect size and the, 153–155 Statistical tables: computer software programs, 417 table F.1; critical values of chi-square, 405 table E; critical values of F, 405–413, critical values of r, 403–404 table D; critical values of t, 402; distribution of z, 398–401 table B; random numbers, 396–397 table A; table A; statistical power, 414 table G Statistically (non)significant, See Null hypothesis Statistics: explanation of, 346–347 Stem and leaf plot, 116, 118 and fig 6.3 Stephen, A T., 222 Stepwise multiple regression, 378 Sternberg, R J., 295 Stevens, J., 383 Strack, F., 109 Strata, 111 Stratified sampling, 111, 112 Stroebe, W., 281 Structural equation analysis, 176–177, 178 fig 9.6; 388–389, 390 fig D.1 Structured interviews, 108 Student’s t, 355 Suci, G J., 77 Sullivan, G L., 136 Sullivan, L A., 73 Sum of squares, 121, 351, 367–368 Summation notation, 347–348 Surveys: “current concerns,”15 fig 1.1; explanation of, 14; goal of, 107; procedures for, 107, 108; sample data, 115 table 6.2; use of existing, 109 See also Self-report measures Suspicion check, 55 Systematic error, 89–90 and fig 5.1 Systematic observation, 134 Systematic random sampling, 111 T test, 192 Tabachnick, B G., 383 Tannenbaum, P H., 77 Tassinary, L G., 82 Tautological theories, 37 Teachman, B., 84 Temporal priority, 185 Test-retest reliability, 91–92 Thematic Apperception Test (TAT), 73 Theories, 35–37 Thesaurus, 32 Thibodeau, R., 81 Think-Aloud Protocols, 73 See also Variables Thoeny, A R., 17 Thomas, G., 57 Time sampling, 135 Time-series designs, 281–282 and fig 14.2, 283 Traits, 92 See also Conceptual variables Tranel, D., 286 Traugott, M W., 109 Trimming, 345 True score, 93 Tukey Honestly Significant Difference (HSD) Test, 382–383 Tukey, J W., 345 Twenge, J M., 265 Two-sided p-values, 148–149 × experimental design, See Factorial experimental designs Type errors, 150–151, 152–153, 219, 271 See also Null hypothesis Type errors, 150–152, 153 See also Null hypothesis Tyrrell, D A J., 81 U.S Census Bureau, 109 Unacknowledged participant, 130–131 Unbiased estimator, 354 Univariate statistics, 383 Unrelated-experiments technique, 244 Unstructured interviews, 108 Valid research: definition of, 228; threats to, 228, 229 and table 12.1 See also Construct validity; External validity; Internal validity; Null hypothesis Validity: comparing reliability and, 101– 102; types of, 95–99, 100 table 5.2 Values, 8–10, 11 Variables: analysis of, 190; in correlational research, 173–177; deleting, 344–346; distribution of the, 118; explanation of, 16; graph of, 161 fig 9.1; histogram, 116, 117 fig 6.2; relationship between, 161; relationships of, 71; types of, 37–38; validations of, 89–100 Variance, 118, 121, 190–191, 352 Vaughan, T R., 43 Walder, L O., 174 Walker, C., 203 Wall, S., 136 Waters, E., 136 Websites: American Psychological Association (APA), 31; computer software packages, 417 statistical table F.1 Webb, E J., 79 Weick, K E., 134 Wells, G L., 82, 135 West, S G., Westling, B E., 84 Whyte, W F., 131, 132 Williams, K D., 199 Wilson, T D., Wisneski, D., 179 Within-groups variance, 191 Within-participants design, 193, 194 Woods, S W., 84 Word, C O., 82 Wrightsman, L S., 102 χ2, See Chi–square Yates, F., 401, 402, 404, 405 Young, R D., 46 Young, R M., 268 Z score, 352–353 and fig B.2 Zajonc, R B., 29, 252 Zanna, M P., 82 Zedeck, S., 380, 383 Zimbardo, P G., 34, 270 FIGURE D.2 Choosing a Statistical Analysis BEGIN IV = independent variable Is there more than one variable? DV = dependent variable No Descriptive statistics No Descriptive statistics Yes Are there an IV and a DV? Yes Yes No Is there more than one IV? Is the IV nominal? Are all of the IVs nominal? Yes No No Yes Is the DV nominal? Multiple regression Pearson correlation Is the DV nominal? Yes No No Yes Loglinear analysis Factorial ANOVA One-way ANOVA Chi square [...]... coffee over the interviewer’s desk during the interview, whereas for others no such event was mentioned After reading the information, the students first judged the woman they had read about in terms of her suitability for the job on rating scales such as how much they liked her and how intelligent they thought she was They also indicated how they thought each of the behaviors they had read about (for instance,... Humans Appendix A: The sample research report and reference formats have been updated to conform to the “sixth edition” of the American Psychological Association Publication Guide xx PREFACE Supplements to the Text The following supplementary materials are available with Research Methods for the Behavioral Sciences Contact your local Cengage Learning representative for more information For Instructors:... updates, the fourth edition of Research Methods for the Behavioral Sciences has added a new feature, Current Research in the Behavioral Sciences, to provide students with examples of new research studies These studies can be used as discussion points to help students learn about current trends in behavioral research, and may also be used as background readings for students who are looking for project... “scientific” as research in the natural sciences Even though behavioral research has not advanced as far as research in the natural sciences, behavioral scientists follow the same procedures as do scientists in other fields These procedures involve creating a systematic set of knowledge about the characteristics of individuals and groups and the relationships among them In this sense, behavioral science research. .. New Feature: Current Research in the Behavioral Sciences: Using Feelings in the Ultimatum Game Chapter 13: New Feature: Current Research in the Behavioral Sciences: A Meta-Analysis of the Effectiveness of Current Treatment Approaches for Withdrawal From Tranquilizer Addictions Chapter 14: New Feature: Current Research in the Behavioral Sciences: Damage to the Hippocampus Abolishes the Cortisol Response... effects of the behaviors on the judgments were compared to the students’ reports about how the behaviors influenced their judgments, the researchers found that the students were not always correct Although the students were aware that information about strong academic credentials increased their judgments of intelligence, they had no idea that the applicant’s having spilled coffee made them like her... conducting research is fun! If you have ever wondered about how we learn and why we forget, what dreams are for and whether they influence us when we are awake, whether we can tell if others are lying to us, or even whether some people have extrasensory perception (ESP), you will find that behavioral research is the best way to provide answers to these interesting questions Studying behavioral research. .. Limitations of Using Intuition The Scientific Method Values Versus Facts in Scientific Research Basic and Applied Research The Importance of Studying Research Methods Evaluating Research Reports Conducting Research Thinking Critically About Research Research Designs: Three Approaches to Studying Behavior Descriptive Research: Assessing the Current State of Affairs Correlational Research: Seeking Relationships... measurement.1 Behavioral scientists draw their conclusions about human behavior from systematic collection and analysis of data Behavioral scientists believe that research is the best tool for understanding human beings and their relationships with others For instance, rather than accepting the claim of a religious leader that the adoption of traditional religious beliefs will change behavior, a behavioral. .. handbook for students working as research assistants or writing theses Indeed, I use the textbook as a test for my graduate students—if they know everything in it, I can trust that they will be able to fully and adequately analyze their data or be able to realize what other information they might need to do so Furthermore, I wanted a book that is balanced in emphasis between conducting and consuming research ... Interpreting the data What is the meaning of the data? What are the important conclusions of the research? What are the limitations of the research? What are the implications of the research for everyday... summarizes these relationships Research Goals and Questions Section of the Research Report Creating the research hypothesis What is the research problem? Why is the research important? What are the. .. are the goals of the research? What is the relationship of this research to previous research? What is the research hypothesis? INTRODUCTION Creating the research design What research design should