Skip to:Content
|
Bottom
Cover image for Research methods and statistics : an integrated approach
Title:
Research methods and statistics : an integrated approach
Personal Author:
Publication Information:
Fort Worth : Harcourt, 2000
ISBN:
9780155071629

Available:*

Library
Item Barcode
Call Number
Material Type
Item Category 1
Status
Searching...
30000010150669 Q180.55.M4 F87 2000 Open Access Book Book
Searching...
Searching...
30000005161066 Q180.55.M4 F87 2000 Open Access Book Book
Searching...

On Order

Summary

Summary

This book was written in response to the needs for a growing number of schools that are teaching an integrated research methods/statistics course. Basic Research Methods and Statistics has detailed, comprehensive and even-handed coverage of the fundamental issues in research design and data analysis, and is written in a conversational style that students can easily comprehend. The text is comprehensive in its coverage of basic and intermediate topics, however, the modular format allows professors to skip or rearrange the order of chapters without loss of continuity. Therefore, the text is appropriate for either a one-semester or two-semester course.


Table of Contents

Prefacep. v
Chapter 1

p. 2

An Introductory Overviewp. 3
Ways of Knowingp. 4
Intuition and Reasoning Versus Empirical Observation: An Examplep. 7
The Scientific Methodp. 10
Characteristics of Scientific Observationsp. 11
Rival Explanationsp. 14
Defining the Termsp. 14
Replicationp. 15
Internal and External Validityp. 15
Conducting a Research Studyp. 16
Exercisesp. 19
Chapter 2

p. 22

Ethics in Researchp. 23
Guidelines for Psychologistsp. 24
The Basic Ethical Dilemmap. 25
The Six General Ethical Principlesp. 27
Specific Ethical Issues in Research with Humansp. 28
Risk or Freedom From Harmp. 28
Informed Consentp. 29
Debriefingp. 32
Privacyp. 32
Ethical Treatment of Animals as Research Subjectsp. 33
Special Issues About the Ethics of Researchp. 34
Who Decides What Is "Right?"p. 34
Ethics of Fundingp. 34
Ethics and Statisticsp. 35
What Becomes of What You Find?p. 36
A Final Note for New Researchersp. 38
Exercisesp. 38
Chapter 3

p. 40

Variablesp. 41
Variables Versus Constants: Definitions and Examplesp. 42
How to Identify Variables Versus Constantsp. 44
Types of Variablesp. 45
Types of Relationshipsp. 47
No Relationshipp. 47
Correlationp. 47
Causalityp. 49
Necessary, Sufficient, and Contributory Causesp. 50
Simple Versus Multiple Causationp. 51
Exercisesp. 53
Chapter 4

p. 56

Measuring Variablesp. 57
Data-Gathering Techniquesp. 58
Behavioral Observationsp. 58
Self-Reportsp. 58
Behavioral Ratingsp. 60
Archival Recordsp. 60
Physical Trace Approachp. 61
Measurementp. 62
Operational Definitions: Measuring Variablesp. 63
Operational Definitions: Establishing Research Conditionsp. 64
Reliability and Validityp. 66
Reliabilityp. 66
Validityp. 69
Levels (or Scales) of Measurementp. 72
Sensitivity of Measurementsp. 75
Exercisesp. 75
Chapter 5

p. 78

Descriptive Statisticsp. 79
Populations and Samplesp. 80
About the Computations in This Textp. 80
Frequencyp. 81
Graphing Frequenciesp. 82
Grouped Frequenciesp. 84
Probabilityp. 86
Central Tendencyp. 89
Modep. 89
Medianp. 89
Meanp. 93
Means Versus Medians: The Case of Outliersp. 94
Distributions of Scoresp. 95
The Normal Distributionp. 96
Skewed Distributionsp. 97
Variabilityp. 98
Variance and Standard Deviationp. 98
Median Absolute Deviationp. 101
Standard Deviations Versus the Median Absolute Deviation: The Case of Outliersp. 104
Rangep. 105
Number of Categories/Valuesp. 105
The Variation Ratiop. 106
Selecting Appropriate Descriptive Statisticsp. 106
Simple Data Transformationsp. 106
z-Scoresp. 112
z-Scores as Inferential Statistics: Areas Under the Normal Curvep. 114
Exercisesp. 120
Chapter 6

p. 124

Hypothesis Testingp. 125
Representativeness and Sampling Proceduresp. 127
Random Samplingp. 127
Stratified Random Samplingp. 129
Available Samples and Convenience Samplingp. 129
Statistical Hypothesesp. 130
The Null Hypotheses (H[subscript 0])p. 130
Research or Alternate Hypothesis (H[subscript 1])p. 131
Sampling Distributionsp. 133
The Shape of the Sampling Distributionp. 136
The Average of the Sampling Distributionp. 138
Variability of Sampling Distributionsp. 138
Probabilities of Samplesp. 139
Making the Decisionp. 140
Significance Levels ([alpha])p. 142
Critical Valuesp. 143
Tables of Critical Valuesp. 144
Have We Made the Correct Decision?p. 145
Threats to the Validity of Hypothesis-Testing: Pitfalls to Avoidp. 149
Statistical Versus Practical and Psychological Significancep. 149
The Relevant Error Rate and "Accepting" The Null Hypothesisp. 150
The Arbitrary Cut-off Point Between "Rare" and "Common" Eventsp. 151
Proposed Alternatives to the Null-Hypothesis-Testing Procedurep. 152
A Call for Compromise: Using a Combination of Approachesp. 153
Exercisesp. 154
Chapter 7

p. 156

General Research Methodsp. 157
The Experimental Methodp. 158
The Logic of Experimentsp. 160
An Overview of the Experimental Methodp. 166
An Alternative to Random Assignment: Repeated Measuresp. 169
Research Settings for Experiments: Laboratory Versus Field Experimentsp. 169
Quasi-Experimental Research Methodsp. 171
Non-Equivalent Groups Designsp. 171
Time-Series Designsp. 173
Two Approaches to Analyzing the Resultsp. 174
Summary of Quasi-Experimental Methodsp. 175
Correlational Methodsp. 175
Naturalistic Observationp. 178
Summary of the Correlational Methodp. 180
Exercisesp. 181
Chapter 8

p. 184

Correlation Coefficientsp. 185
Magnitudep. 186
Directionp. 188
Graphing the Relationship Between Two Variablesp. 189
Selecting the Appropriate Correlation Coefficientp. 191
Pearson Product-Moment Correlation Coefficientp. 193
The Pearson r as an Inferential Statistic: Testing the Null Hypothesisp. 196
Spearman Rank-Order Correlation Coefficientp. 197
The Spearman r as an Inferential Statistic: Testing the Null Hypothesisp. 199
Tied Ranking Procedurep. 200
Correlating Nominal Datap. 202
Phi Coefficientp. 203
Testing the Difference Between Two Correlationsp. 206
Exercisesp. 208
Chapter 9

p. 212

Introduction to Regression Analysisp. 213
The Logic Behind Simple Regression Analysisp. 214
The Regression Equationp. 217
About the Regression Equationp. 219
Assumptions and Limitations of the Least-Squares Method of Regressionp. 221
Linearityp. 222
Normal Distributions and Homoscedasticityp. 224
Evaluating Y': How Accurate Are Our Predictions?p. 227
A Short-Cut for Computing the Standard Error of the Estimatep. 235
z-Scores and Regression Analysisp. 236
Coefficient of Determinationp. 238
Using Venn Diagrams to Illustrate r[superscript 2]p. 241
The Basic Concepts of Multiple Regressionp. 242
Using Venn Diagrams to Illustrate Multiple Regression and R[superscript 2]p. 243
Multicollinearityp. 246
Exercisesp. 248
Chapter 10

p. 252

Designing Experiments and Quasi-Experimentsp. 253
One-way Designsp. 255
Factorial Designs and the Concept of Interaction: "It Depends"p. 256
Multiple Determinants (or Predictors) of Behaviorp. 257
Contingencies Among Determinants: The Essence of Interactionp. 258
Terminology and Notation Systems for Factorial Designsp. 261
Factorial Designs and Confoundsp. 263
The Research Questions Addressed in Factorial Designsp. 264
Selecting Only the Necessary Independent Variablesp. 267
Selecting the Necessary Levels of the Independent Variablesp. 268
No-Treatment Control Groupp. 271
Placebo Control Groupsp. 272
Research Designsp. 273
Comparisons Between Groups Versus Repeated Measuresp. 273
Testing Participants Repeatedly in Within-Subjects Designsp. 273
Advantages of Within-Subjects Designsp. 275
Disadvantages of Within-Subjects Designsp. 277
Counterbalancingp. 279
Summary of Within-Subjects Designsp. 285
Advantages and Disadvantages of Between-Subjects Designsp. 285
Matching Designsp. 286
Some General Confounds: Threats to Internal Validityp. 287
Maturationp. 287
Historyp. 288
Regression Toward the Meanp. 288
Instrumentationp. 289
Mortalityp. 290
Sensitizationp. 290
Pretest-Posttest Designs: The Need for a Control Groupp. 291
Selecting Within-Subjects Factors for Mixed Designsp. 294
The Special Case of Age as an Independent Variablep. 297
Steps in Designing an Experiment or Quasi-Experimentp. 298
Exercisesp. 300
Chapter 11

p. 306

The z-Test and t-Test: Analyzing Data from One-and Two-Group Designsp. 307
The z-Test: When the Population Standard Deviation ([sigma]) Is Knownp. 308
z-Test: Application 1: When the Population Mean ([mu]) Is Knownp. 308
z-Test Application 2: When the Population Mean ([mu]) Is Being Testedp. 317
Requirements for the z-Testp. 318
The t-Test: When the Population Standard Deviation ([sigma]) Is Unknownp. 320
One-Sample t-Testp. 322
Two-Sample t-Test: Independent Samples From a Between-Subjects Designp. 326
Two-Sample t-Test: Related Samples From a Within-Subjects or Matching Designp. 333
The Limited Applicability of z- and t-Testsp. 338
Exercisesp. 339
Chapter 12

p. 342

Analysis of Variancep. 343
Sources of Variationp. 345
Between-Subjects Designsp. 345
Within-Subjects Designsp. 346
Factorial Designsp. 347
Mixed Designsp. 347
Computing Sums of Squaresp. 349
One-way BS-ANOVAp. 349
Two-way BS-ANOVAp. 353
One-way RM-ANOVAp. 356
Degrees of Freedomp. 359
Mean Squaresp. 364
The F-Ratiop. 365
Testing the Significance of Fp. 366
Post Hoc Analysesp. 367
Dunn's Multiple Comparisons Procedurep. 368
Appendix 12-A Example of a One-way BS-ANOVAp. 373
Appendix 12-B Example of a 2 [times] 3 (Two-way) BS-ANOVAp. 379
Appendix 12-C Example of a One-way RM-ANOVAp. 391
Exercisesp. 399
Chapter 13

p. 406

Nonparametric Tests for Experiments and Quasi-Experimentsp. 407
Nominal Scalesp. 410
Between-Subjects Designs: Chi-Square (X[superscript 2])p. 410
Within-Subjects Designs: Cochran's Qp. 416
Ordinal Scalesp. 422
Between-Subjects Designs: The Wilcoxon Rank Sum Test and the Kruskal-Wallis Hp. 422
Within-Subjects Designs: Wilcoxon Signed Ranks Test (a.k.a. the Wilcoxon W)p. 428
A Cautionary Note about When to Select the Appropriate Statisticp. 431
Exercisesp. 432
Chapter 14

p. 438

Estimation and Confidence Intervalsp. 439
Confidence Intervals for the Meanp. 441
Finding the Margin of Error: The Maximum Error of the Estimatep. 441
Confidence Interval: The Range of Likely Values of the Population Meanp. 445
Summary: Steps in Computing the Confidence Interval for the Meanp. 447
Confidence Intervals for Proportions (or Percentages)p. 447
Numerical Examples of Confidence Intervals for Proportions (or Percentages)p. 448
Limitations of Confidence Intervals for Proportions (or Percentages)p. 450
Confidence Intervals for Pearson Correlationsp. 451
Numerical Example of Confidence Intervals for the Pearson Correlationp. 453
Minimum Differences Between Treatment Meansp. 455
Minimum Differences in Two-Group Between-Subjects Designsp. 456
Minimum Differences in Two-Treatment Related-Samples Designsp. 460
Confidence Intervals Versus Significance Testingp. 464
Numerical Example of Confidence Intervals That Do Not Overlapp. 466
Numerical Example of Confidence Intervals That Overlapp. 467
Confidence Intervals and Statistical Powerp. 471
Renewing the Call for Compromise: Combining the Approachesp. 475
Exercisesp. 475
Chapter 15

p. 478

Single-Subject Research Designp. 479
Key Elements of Single-Subject Researchp. 480
Elements of Measurementp. 481
Design Phases in Single-Subject Research Designsp. 486
Presentation of Datap. 486
Threats to the Validity of Data from Single-Subject Designsp. 488
Specific Research Designsp. 490
ABAB Designsp. 490
Multiple-Baseline Designsp. 493
The Changing Criterion Designp. 498
Alternating Treatment Designsp. 501
Mixed Designsp. 504
Single-Subject Designs for Applied and Basic Research Questionsp. 506
Evaluation of Data from Single-Subject Designsp. 507
Visual Inspectionp. 508
Interpreting the Data from Single-Subject Researchp. 514
Potential Confounds and Problems in the Visual Interpretation of Datap. 516
Resources for Further Studyp. 518
Exercisesp. 519
Chapter 16

p. 524

Qualitative Research Methods and Analysisp. 525
Qualitative Methods for Gathering Datap. 526
Observationp. 527
Interviewsp. 532
Textual Analysisp. 539
Transcriptionp. 540
Reliability and Validity in Qualitative Researchp. 542
Triangulation of Methods: Increasing the Validityp. 543
A Case Study Illustrating Triangulation of Qualitative Research Methodsp. 544
Statistics for Qualitative Methodsp. 546
The Future of Qualitative Methodsp. 548
Suggestions for Further Readingp. 548
Exercisesp. 549
Appendix Ap. 0
Ethical Principles of Psychologists and Code of Conductp. 1
Introductionp. 3
Preamblep. 5
General Principlesp. 5
Principle A Competencep. 5
Principle B Integrityp. 6
Principle C Professional and Scientific Responsibilityp. 6
Principle D Respect for People's Rights and Dignityp. 6
Principle E Concern for Others' Welfarep. 6
Principle F Social Responsibilityp. 7
Ethical Standardsp. 7
1. General Standardsp. 7
2. Evaluation, Assessment, or Interventionp. 13
3. Advertising and Other Public Statementsp. 15
4. Therapyp. 16
5. Privacy and Confidentialityp. 19
6. Teaching, Training Supervision, Research, and Publishingp. 21
7. Forensic Activitiesp. 26
8. Resolving Ethical Issuesp. 28
Appendix Bp. 0
Statistical Tablesp. 1
Appendix Cp. 0
Introduction to Statistical Powerp. 1
Two Variancesp. 1
Using the Two Variances to Test the Null Hypothesisp. 3
Statistical Powerp. 5
Maximizing the Power in a Studyp. 7
Adequate Sample Sizep. 7
Lower Significance ([alpha]) Levelsp. 9
Selecting Designs with More Inherent Powerp. 9
Power Analysisp. 14
Exercisesp. 20
Appendix Dp. 0
Reporting the Researchp. 1
Methods of Disseminationp. 1
Presentations at Professional Meetingsp. 1
Written Reportsp. 4
Electronic Disseminationp. 5
General Writing Stylep. 6
Some Specific Issues and Common Errorsp. 8
Re-writingp. 9
Plagiarismp. 10
APA Format and Manuscript Preparationp. 11
Sections of an APA-Format Research Reportp. 12
Examples of References Using the APA Formatp. 19
Manuscript Headingsp. 23
Sample Manuscriptsp. 24
Appendix Ep. 0
Answers for the Odd-Numbered Exercisesp. 1
Appendix Fp. 0
Referencesp. 1
Glossaryp. 1
Indexp. 1
Go to:Top of Page