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Research Design Explained (with InfoTrac)

ISBN: 9780534617318 | 053461731X
Edition: 5th
Format: Paperback
Publisher: Wadsworth Publishing
Pub. Date: 7/23/2003

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Preface. 1. PSYCHOLOGY AND SCIENCE. Overview. Why Psychology Uses the Scientific Approach. The Characteristics of Science. The Characteristics of Psychology. The Importance of Science to Psychology. Questions About Applying Techniques From Older Sciences to Psychology. Internal Validity Questions: Did the Treatment Cause a Change in Behavior? Construct Validity Questions: Making the Leap From the Physical World to the Mental World? External Validity Questions: Can the Results Be Generalized? Ethical Questions: Should the Study Be Conducted? Conclusions About the Questions That Researchers Face. Why You Should Understand Research Design. To Understand Psychology. To Read Research. To Evaluate Research. To Protect Yourself From "Quacks." To Be a Better Thinker. To Be Scientifically Literate. To Increase Your Marketability. To Do Your Own Research. Concluding Remarks. Summary. Key Terms. Exercises. Web Supplements. 2. GENERATING AND REFINING RESEARCH HYPOTHESES. Overview. Generating Research Ideas From Common Sense. Generating Research Ideas From Previous Research. Specific Strategies. Conclusions About Generating Research Ideas From Previous Research. Converting an Idea Into a Research Hypothesis. Make It Testable. Make It Supportable. Be Sure to Have a Rationale: How Theory Can Help. Demonstrate Its Relevance: Theory Versus Trivia. Refine It: 10 Time-Tested Tips. Make Sure That Testing the Hypothesis Is Both Practical and Ethical. Changing Unethical and Impractical Ideas Into Research Hypotheses. Make Variables More General. Use Smaller Scale Models of the Situation. Carefully Screen Potential Participants. Use "Moderate" Manipulations. Do Not Manipulate Variables. Concluding Remarks. Summary. Key Terms. Exercises. Web Supplements. 3. READING AND EVALUATING RESEARCH. Overview. Reading for Understanding. Choosing an Article. Reading the Abstract. Reading the Introduction. Reading the Method Section. Reading the Results Section. Reading the Discussion. Developing Research Ideas From Existing Research. The Direct Replication. The Systematic Replication. The Conceptual Replication. The Value of Replications . Extending Research. Concluding Remarks. Summary. Key Terms. Exercises. Web Supplements. 4. MEASURING AND MANIPULATING VARIABLES: RELIABILITY AND VALIDITY. Overview. Choosing a Behavior to Measure. Errors in Measuring Behavior. Overview of Two Types of Measurement Errors: Bias and Random Error. Errors due to the Observer: Bias and Random Error. Errors in Administering the Measure: Bias and Random Error. Errors Due to the Participant: Bias and Random Error. Summary of the Three Sources and Two Types of Measurement Error. Reliability: The (Relative) Absence of Random Error. The Importance of Being Reliable: Reliability as a Prerequisite to Validity. Using Test-Retest Reliability to Assess Overall Reliability: To What Degree Is a Measure "Random Error Free"? Identifying (and Then Dealing With) the Main Source of a Measure''s Reliability Problems. Conclusions About Reliability. Beyond Reliability: Establishing Construct Validity. Content Validity: Does Your Test Have the Right Stuff? Internal Consistency Revisited: Evidence That You Are Measuring One Characteristic. Convergent Validation Strategies: Statistical Evidence That You Are Measuring the Right Construct. Discriminant Validation Strategies: Showing That You Are Not Measuring the Wrong Construct. Summary of Construct Validity. Manipulating Variables. Common Threats to a Manipulation''s Validity. Evidence Used to Argue for a Manipulation''s Construct Validity. Pros and Cons of Three Common Types of Manipulations. Conclusions About Manipulating Variables. Concluding Remarks. Summary. Key Terms. Exercises. Web Supplements. 5. BEYOND RELIABILITY AND VALIDITY: CHOOSING THE BEST MEASURE FOR YOUR STUDY. Overview. Sensitivity: Will the Measure Be Able to Detect the Differences You Need to Detect? Achieving the Necessary Level of Sensitivity. Conclusions About Sensitivity. Scales of Mea

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