This text successfully integrates statistics and research methods, by placing statistics in the context of research to help students grasp both topics more clearly. Discussions include all major descriptive and experimental methods, as well as primary and secondary statistical procedures.

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Gary Heiman is a professor at Buffalo State College. 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. He received his Ph.D. in cognitive psychology from Bowling Green State University.

Note: Each chapter concludes with Putting It All Together, Chapter Summary, Key Terms, Review Questions, and Practice Problems. I. Introduction to Psychological Research 1. Introduction to the Scientific Method Introduction (Or Why Am I Here?) The Scientific Method The Goals of Psychological Research Scientific Hypotheses The Flaws in Scientific Research 2. The Logic of Designing and Interpreting Research Beginning the Design: Asking the Question Testing a Hypothesis by Discovering a Relationship The Role of Statistical Procedures Summary of the Flow of a Study Experimental Research Methods Descriptive Research Methods 3. Understanding Reliability and Validity Designing an Example Study Critically Evaluating the Study Understanding Reliability Understanding Validity Minimizing Threats to Validity and Reliability Issues of Validity and Reliability in Descriptive Studies Issues of Validity and Reliability in Experiments 4. Design Issues and Ethical Concerns in Experiments Two Example Studies Designing the Independent Variable Designing the Dependent Variable Controlling Extraneous Variables Demand Characteristics Research Involving Animals Research Ethics 5. Design Issues and Ethical Concerns in Descriptive Research The Uses of Descriptive Research Observational Studies Field Surveys Types of Sampling Techniques Designing Interviews and Questionnaires Ethical Issues in Descriptive Research II. Descriptive Statistics 6. Summarizing Research Using Frequency Distributions and Percentiles More Statistical Notation Types of Measurement Scales Creating Simple Frequency Distributions Types of Simple Frequency Distributions Creating Relative Frequency Distributions Types of Relative Frequency Distributions Computing Percentile A Word About Grouped Frequency Distributions Summary of Formulas 7. Summarizing Research Using Measures of Central Tendency More Statistical Notation Understanding Central Tendency The Mode The Median The Mean Using the Mean in Research Summarizing Research Using Central Tendency Designing a Powerful Experiment APA Format for Statistical Notation Summary of Formulas 8. Summarizing Research Using Measures of Variability More Statistical Notation Understanding Variability Describing the Sample Variance Describing the Sample Standard Deviation The Population Standard Deviation and the Population Variance Variance as the Error in Predictions Summarizing Research Using the Mean and Standard Deviation APA Format for Statistical Notation Summary of Formulas 9. Summarizing Research Using z-Scores More Statistical Notation Understanding z-Scores Interpreting z-Scores: The z-Distribution Using the z-Distribution to Compare Different Distributions Using the z-Distribution to Describe Individual Scores Using z-Scores to Describe Sample Means APA Format for Statistical Notation Summary of Formulas III. Correlational Research and Correlational Statistics 10. Correlational Research and the Correlation Coefficient More Statistical Notation Understanding Correlational Research Distinguishing Characteristics of Correlational Analysis Types of Relationships Strength of the Relationship Using the Correlation Coefficient in Research Computing the Correlation Coefficient Creating a Powerful Correlational Design Correlations in the Population APA Format for Statistical Notation Summary of Formulas 11. Using Linear Regression to Predict Scores More Statistical Notation Understanding Linear Regression The Linear Regression Equation Describing Errors in Prediction When Using the Linear Regression Equation Predicting Variability: The Proportion of Variance Accounted For A Word About Multiple Correlation and Regression APA Format for Statistical Notation Summary of Formulas IV. Introduction to Inferential Statistics 12. Probability and Making Decisions About Chance Events More Statistical Notation The Logic of Probability Computing Probability Obtaining Probability From the Standard Normal Curve Making Decisions Based on Probability Making Decisions About a Sample Mean Summary of Formulas 13. Overview of Statistical Hypothesis Testing: The z-Test More Statistical Notation The Role of Inferential Statistics in Research Setting Up Inferential Procedures Testing a Mean When sX is Known: The z-Test Interpreting zobt Summary of Statistical Hypothesis Testing The One-Tailed Test Errors in Statistical Decision Making APA Format for Statistical Notation Summary of Formulas 14. The Single-Sample Study: Testing a Sample Mean or Correlation Coefficient More Statistical Notation Understanding the t-Test for a Single-Sample Mean Calculating the Single-Sample t-Test Estimating the Population m by Computing a Confidence Interval Summary of the t-Test Significance Tests for Correlation Coefficients Summary of Testing a Correlation Coefficient Maximizing the Power of the t-Test and Correlation Coefficient APA Format for Statistical Notation Summary of Formulas V. Designing and Analyzing Two-Sample Experiments 15. The Two-Sample Between-Subjects Experiment and the Independent-Samples t-Test More Statistical Notation Designing the Two-Sample Experiment Controlling Participant Variables in a Between-Subjects Design The Independent-Samples t-Test Describing the Relationship in a Two-Sample Experiment Power and the Independent Samples t-Test Eliminating Participants from the Data APA Format for Statistical Notation Summary of Formulas 16. The Two-Sample Within-Subjects Experiment and the Dependent-Samples t-Test More Statistical Notation Designs That Directly Control Participant Variables Choosing a Design The Dependent-Samples t-Test Power and the Dependent-Samples t-Test APA Format for Statistical Notation Summary of Formulas VI. Designing and Analyzing Complex Experiments 17. The One-Way Between-Subjects Experiment and the One-Way Analysis of Variance More Statistical Notation Designing Multilevel Experiments Overview of ANOVA Components of the F-Statistic Computing the F-Ratio Performing Post Hoc Comparisons Summary of the Steps in Performing a One-Way ANOVA Describing the Relationship in a One-Way ANOVA Power and the ANOVA APA Format for Statistical Notation Summary of Formulas 18. The Two-Way Between-Subjects Experiment and the Two-Way Analysis of Variance More Statistical Notation The Reason for Multifactor Studies Overview of the Two-Way ANOVA Computing the Two-Way ANOVA Interpreting the Two-Way Experiment Summary of the Steps in Performing a Two-Way ANOVA APA Format for Statistical Notation Summary of Formulas 19. Within-Subjects Experiments and Other Multifactor Designs Controlling Participant Variables in Complex Designs The One-Way Within-Subjects Analysis of Variance The Two-Way Within-Subjects Design The Two-Way Mixed Design The Three-Way Design The Test for Homogeneity of Variance: The Fmax Test Other Ways to Compare the Means in a Factorial Design Going Beyond the Analysis of Variance APA Format for Statistical Notation Summary of Formulas VII. Alternative Approaches to Design and Analysis 20. Quasi-Experiments and Single-Subject 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 Understanding Small N Research and the Single-Subject Design A Word About Program Evaluation 21. Chi Square and Other Nonparametric Statistical Procedures The Reasons for Using Nonparametric Procedures Chi Square Procedures The One-Way Chi Square: The Goodness of Fit Test The Two-Way Chi Square: The Test of Independence Nonparametric Procedures for Ranked Data APA Format for Statistical Notation Summary of Formulas Appendixes A. Organizing and Communicating Research Using APA Format B. Additional Statistical Formulas C. Statistical Tables D. Answers to Odd-Numbered Review Questions and Practice Problems

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