### Summary

Basic Statistics for the Behavioral Sciencesdemystifies and fully explains statistics without leaving out relevant topics or simply presenting formulas, in a format that is non-threatening and inviting to students. Gary Heiman has written a textbook--clearly, patiently, and with an occasional touch of humor--that teaches students not onlyhowto compute an answer on demand, but alsowhythey should perform the procedure or what their answer reveals about the data. Heiman has achieved five objectives in writing this text: to take a conceptual-intuitive approach, to present statistics within an understandable research context, to deal directly and positively with student weaknesses in mathematics, to introduce new terms and concepts in an integrated way, and to create a text that students will enjoy as well as learn from! New!Chapter 1 has been significantly revised to make it more student friendly and current. New!Appendix B explains the basics of how to use SPSS to analyze data. Tips on using SPSS are integrated throughout the text and now have a specific index to guide students. New! A Quick Reviewfeature from Heiman'sEssentialstext has been added to this edition. Each contains a simple review of previous concepts, additional examples, and study questions. New!A new section on Statistics in Published Research has been added to help students gain a perspective on how researchers use statistics and relates what students have learned in the chapter to what they will see (and won't see) when reading published research. (Includes using the APA format for stats.) Getting Startedsection at the beginning of each chapter lists previously discussed concepts that students should review, followed by the learning goals for the chapter. New! Statistical Notationsections introduce statistical notations at the beginning of relevant chapters in which they are needed. For added clarity, statistical notations are introduced separately from the conceptual issues presented in the chapter. Remembercallout sections provide added reinforcement by reviewing the calculation or interpretation of a statistic and emphasizing each procedural point. Computation formulas are labeled and highlighted in color throughout the text. Putting It All Togethersections at the end of each chapter provide advice, cautions, and ways to integrate material from different chapters. Chapter Summaryprovides a substantive review of the material, not merely a list of the topics covered. Summary of Formulasat the end of each chapter serves as a quick reference. Reference tables in the front endpages provide guidelines for selecting from the descriptive and inferential procedures discussed in the text based on the type of data or research design employed. References to "psychology" have been reduced so that the text pertains to other behavioral sciences as well. An engaging, non-threatening writing style and step-by-step conceptual approach support math-anxious students. Reduced repetitiveness, wordiness, and protracted explanations in this extensive revision have streamlined the narrative, without sacrificing content or comprehension. Conceptual presentations have been tightened and a number of new explanatory techniques have been added. Throughout, greater emphasis is placed on explaining how to use statistics and how to "think" in statistical terms Pedagogically effective use of examples includes in nearly all examples specific variables and research questions instead of generic data. Many early examples are taken from everyday life, so that students have an intuitive feel for the meaning of the scores and relationships discussed. In later chapters, examples become more technical and "psychological." The text provides clear explan

### Table of Contents

Contents Note: Each Chapter begins with Getting Started and ends with Putting It All Together, a Chapter Summary, Key Terms, Review Questions, and Application Questions. Chapters 3-15 include a Summary of Formulas. 1. Introduction to Statistics Why Is It Important to Learn Statistics (and How Do You Do That?) Review of Mathematics Used in Statistics 2. Statistics and the Research Process The Logic of Research Samples and Populations Applying Descriptive and Inferential Statistics Understanding Experiments and Correlational Studies The Characteristics of Scores Statistics in Published Research: Using Statistical Terms 3. Frequency Distributions and Percentiles New Statistical Notation Why Is It Important to Know about Frequency Distributions? Simple Frequency Distributions Types of Frequency Distributions Relative Frequency and the Normal Curve Computing Cumulative Frequency and Percentile Statistics in Published Research: APA Publication Rules A Word about Grouped Frequency Distributions 4. Measures of Central Tendency; The Mean, Median, and Mode New Statistical Notation Why Is It Important to Know about Central Tendency? What Is Central Tendency? The Mode The Median The Mean Transformations and the Mean Deviations around the Mean Describing the Population Mean Summarizing an Experiment Statistics in Published Research: Using the Mean 5. Measures of Variability: Range, Variance, and Standard Deviation New Statistical Notation Why Is It Important to Know about Measures of Variability? The Range Understanding the Variance and Standard Deviation Computing the Sample Variance and Sample Standard Deviation The Population Variance and the Population Standard Deviation Summary of the Variance and Standard Deviation Applying the Variance and Standard Deviation to Research Statistics in Published Research: Reporting Variability 6.z-Scores and the Normal Curve Model New Statistical Notation Why Is It Important to Know aboutz-Scores? Understandingz-Scores Interpretingz-Scores Using thez-Distribution Usingz-Scores to Compare Different Variables Usingz-Scores to Determine the Relative Frequency of Raw Scores Statistics in Published Research: Usingz-Scores Usingz-Scores to Describe Sample Means 7. The Correlation Coefficient New Statistical Notation Why Is It Important to Know about Correlation Coefficients? Understanding Correlational Research Types of Relationships Strength of the Relationship The Pearson Correlation Coefficient The Restriction of Range Problem Correlations in the Population Statistics in Published Research: Correlation Coefficients 8. Linear Regression New Statistical Notation Why Is It Important to Know about Linear Regression? Understanding Linear Regression The Linear Regression Equation Describing the Errors in Prediction Computing the Proportion of Variance Accounted For A Word About Multiple Correlation and Regression Statistics in Published Research: Linear Regression 9. Using Probability to Make Decisions about Data New Statistical Notation Why Is It Important to Know about Probability? The Logic of Probability Computing Probability Obtaining Probability from the Standard Normal Curve Random Sampling and Sampling Error Deciding Whether a Sample Represents a Population 10. Introduction to Hypothesis Testing New Statistical Notation Why Is It Important to Know about thez-Tests? The Role of Inferential Statistics in Research Setting Up Inferential Procedures Performing thez-Test Interpreting Significant Results Interpreting Nonsignificant Results Summary of thez-Test Statistics in