Research Methods in Psychology

ISBN-10: 0618170286

ISBN-13: 9780618170289

Edition: 3rd 2002

Authors: Gary Heiman
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Description: Research Methods focuses on decisions and conclusions, rather than rules and procedures, to help students develop the critical-thinking skills necessary for understanding and designing research. The text emphasizes the need to evaluate a design's strengths and weaknesses when selecting a method and interpreting results. The Second Edition includes a full chapter on ethics and places the statistics review after the introduction of basic design issues to focus on statistics as a set of tools for analyzing research results. A unique capstone chapter, Designing and Evaluating Research, walks students through four research studies, summarizes content, and suggests additional topics for research.

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Book details

List price: $293.95
Edition: 3rd
Copyright year: 2002
Publisher: CENGAGE Learning
Publication date: 11/26/2001
Binding: Hardcover
Pages: 544
Size: 7.75" wide x 9.50" long x 1.00" tall
Weight: 1.892
Language: English

Gary Heiman is a professor at Buffalo State College. He received his Ph.D. in cognitive psychology from Bowling Green State University. Praised by reviewers and adopters for his readable prose and effective pedagogical skills, he has written four books for Houghton Mifflin (now Cengage Learning): STATISTICS FOR THE BEHAVIORAL SCIENCES, RESEARCH METHODS IN PSYCHOLOGY, UNDERSTANDING RESEARCH METHODS AND STATISTICS, AND ESSENTIAL STATISTICS FOR THE BEHAVIORAL SCIENCES.

Note: Each chapter begins with Getting Started and concludes with a Chapter Summary, Key Terms, Review Questions, Application Questions, and Discussion Questions
Introduction to Psychological Research
Introduction to the Scientific Method
The Scientific Method
The Goals of Psychological Research Scientific Hypotheses
The Flaws in Scientific Research
An Overview of Creating and Testing Hypotheses
Beginning the Design: Asking the Question
The Research Literature Identifying the Population and Sample
Defining the Terminology in the Hypothesis Testing a Hypothesis by Discovering a Relationship
Interpreting a Relationship Summary of the Flow of a Study Experimental Research
Methods Descriptive Research
Methods Putting It All Together
Evaluating a Study: Is It Reliable and Valid
Identifying Potential Flaws
When Designing a Study Critically Evaluating a Study Understanding Reliability
Understanding Validity
Dealing with Validity and Reliability
When Designing a Study Issues of Validity and Reliability in Descriptive Studies
Issues of Validity and Reliability in Experiments
Selecting a Design Putting It All Together
Creating a Relaibale and Valid Experiment
Selecting the Independent Variable
Selecting the Conditions of the Independent Variable
Selecting the Dependent Variable
Designing the Dependent Variable
Controlling Extraneous Variables
Putting It All Together
Risk, Deception, and the Ethics of Research
Demand Characteristics Research
Ethics Research
Involving Animals Scientific Fraud
Putting It All Together
Controlling Participant Variables
Using Between-Subjects and Within-Subjects
Designs Participant Variables and Individual Differences
How Participant Variables Influence External Validity
How Participant Variables Influence a Relationship
Controlling Participant Variables in a Between-Subjects
Design Controlling Participant Variables in a Within-Subjects
Design Controlling Order
Effects in a Repeated Measures
Design Choosing a Design Putting
It All Together
The Statistical Analysis of Experiments
Applying Descriptive and Inferential Statistics to Simple Experiments
Selecting the Statistical Procedures
Applying Descriptive Statistics to Experiments
Applying Inferential Statistical Procedures
Interpreting Significant Results
Interpreting Nonsignificant Results
Comparing Type I and Type II Errors
Statistical Power and Research
Design Putting
It All Together
Designing and Analyzing
Multifactor Experiments
The Reason for Multifactor Studies
The Two-Way Between-Subjects
ANOVA Using Counterbalanced Variables to Produce Two-Way Designs
The Two-Way Within-Subjects ANOVA
The Two-Way Mixed ANOVA
The Three-Way Design
The Two-Way Chi Square Describing
Effect Size
A Word about Multivariate Statistics and Meta-Analysis
Putting It All Together
Beyond the Typical Laboratory Experiment
Correlational Research and Questionnaire Construction
The Difference Between True Experiments and Correlational Studies
Analyzing Data with Correlational Statistics
Additional Uses of Correlation
Conducting Research
Using Interviews and Questionnaires
A Word about Advanced Correlational Procedures
Putting It All Together
Field Experiments and Single-Subject
Designs Field Experiments
Small N Research and the Single-Subject Design
Putting It All Together
Quasi-Experiments and Descriptive Designs
Understanding Quasi-Experiments
Quasi-Independent Variables
Involving Participant Variables
Quasi-Independent Variables
Involving Environmental Events
The Time-Series Design
The Quasi-Independent Variable of the Passage of Time
Descriptive Research
A Word about Program Evaluation Putting
It All Together
Putting It All Together
A Review: Examples of Designing and Evaluating Research
Sumary of the Issues
When Designing Research
An Experiment on Attribution of Arousal
An Experiment on Time Perception
A Descriptive Study of Fear of Success in Females
An Experimental and Correlational Study of Creativity
Additional Research Topics
Putting It All Together
Appendix A: Reporting Research Using APA Format
An Example Study
The Research Literature Overview of a Research Article
The Components of an APA-Style Research Article
Putting It All Together
Sample APA-Style Research Report
Statistical Procedures
Measures of Central Tendency
Measures of Variability
The Two-Sample t-Test
The One-Way Analysis of Variance
Tukey HSD Post Hoc Comparisons
Measures of Effect Size in t-Tests and ANOVA
Confidence Intervals
Pearson Correlation Coefficient, Linear Regression, and Standard Error of the Estimate
Spearman Correlation Coefficient
Chi Square Procedures
Mann-Whitney U and Wilcoxon T Tests
Kruskal-Wallis H and Friedman X2 Tests
Statistical Tables
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