Statistics for People Who (Think They) Hate Statistics / Edition 6 available in Paperback
Key Features of the Third Edition
-Provides a companion Web site that helps students and professors make the most of the text
-Offers a dynamic and much expanded suite of Instructor’s Resources
-Gives updated examples from a variety of disciplines, and more of them than ever before
-Contains more Time to Practice exercises, with answers in the back of the book
-Presents additional coverage of general research methods basics
-Includes expanded coverage of power
|Edition description:||Sixth Edition|
|Product dimensions:||6.90(w) x 9.90(h) x 0.90(d)|
About the Author
Neil J. Salkind received his Ph D in human development from the University of Maryland, and after teaching for 35 years at the University of Kansas, he was Professor Emeritus in the Department of Psychology and Research in Education, where he collaborated with colleagues and work with students. His early interests were in the area of children’s cognitive development, and after research in the areas of cognitive style and (what was then known as) hyperactivity, he was a postdoctoral fellow at the University of North Carolina’s Bush Center for Child and Family Policy. His work then changed direction to focus on child and family policy, specifically the impact of alternative forms of public support on various child and family outcomes. He delivered more than 150 professional papers and presentations; written more than 100 trade and textbooks; and is the author of Statistics for People Who (Think They) Hate Statistics (SAGE), Theories of Human Development (SAGE), and Exploring Research (Prentice Hall). He has edited several encyclopedias, including the Encyclopedia of Human Development, the Encyclopedia of Measurement and Statistics, and the Encyclopedia of Research Design. He was editor of Child Development Abstracts and Bibliography for 13 years. He lived in Lawrence, Kansas, where he liked to read, swim with the River City Sharks, work as the proprietor and sole employee of big boy press, bake brownies (see www.statisticsforpeople.com for the recipe), and poke around old Volvos and old houses.
Bruce B. Frey, Ph.D., is an award-winning researcher, teacher, and professor of educational psychology at the University of Kansas. He is the author of There’s a Stat for That!, Modern Classroom Assessment, and 100 Questions (and Answers) about Tests and Measurement for SAGE and associate editor of SAGE’s Encyclopedia of Research Design. He also wrote Statistics Hacks for O’Reilly Media. His primary research interests include classroom assessment, instrument development, and program evaluation. In his spare time, Bruce leads a secret life as Professor Bubblegum, host of Echo Valley, a podcast that celebrates bubblegum pop music of the late 1960s. The show is wildly popular with the young people.
Table of Contents
A Note to the Student: Why We Wrote This BookAcknowledgmentsAnd Now, About the Seventh Edition . . .About the AuthorsPART I • YIPPEE! I’M IN STATISTICSChapter 1 • Statistics or Sadistics? It’s Up to You Why Statistics? A 5-Minute History of Statistics Statistics: What It Is (and Isn’t) What Am I Doing in a Statistics Class? Ten Ways to Use This Book (and Learn Statistics at the Same Time!) About the Book’s Features Key to Difficulty Icons Glossary Summary Time to PracticePART II • SIGMA FREUD AND DESCRIPTIVE STATISTICSChapter 2 • Computing and Understanding Averages: Means to an End Computing the Mean Computing the Median Computing the Mode When to Use What Measure of Central Tendency (and All You Need to Know About Scales of Measurement for Now) Using SPSS to Compute Descriptive Statistics Summary Time to PracticeChapter 3 • Understanding Variability: Vive la Différence Why Understanding Variability Is Important Computing the Range Computing the Standard Deviation Computing the Variance Using SPSS to Compute Measures of Variability Summary Time to PracticeChapter 4 • Creating Graphs: A Picture Really Is Worth a Thousand Words Why Illustrate Data? Ten Ways to a Great Figure (Eat Less and Exercise More?) First Things First: Creating a Frequency Distribution The Plot Thickens: Creating a Histogram The Next Step: A Frequency Polygon Other Cool Ways to Chart Data Using the Computer (SPSS, That Is) to Illustrate Data Summary Time to PracticeChapter 5 • Computing Correlation Coefficients: Ice Cream and Crime What Are Correlations All About? Computing a Simple Correlation Coefficient Squaring the Correlation Coefficient: A Determined Effort Other Cool Correlations Parting Ways: A Bit About Partial Correlation Summary Time to PracticeChapter 6 • An Introduction to Understanding Reliability and Validity: Just the Truth An Introduction to Reliability and Validity Reliability: Doing It Again Until You Get It Right Different Types of Reliability How Big Is Big? Finally: Interpreting Reliability Coefficients Validity: Whoa! What Is the Truth? A Last Friendly Word Validity and Reliability: Really Close Cousins Summary Time to PracticePART III • TAKING CHANCES FOR FUN AND PROFITChapter 7 • Hypotheticals and You: Testing Your Questions So You Want to Be a Scientist Samples and Populations The Null Hypothesis The Research Hypothesis What Makes a Good Hypothesis? Summary Time to PracticeChapter 8 • Probability and Why It Counts: Fun With a Bell-Shaped Curve Why Probability? The Normal Curve (aka the Bell-Shaped Curve) Our Favorite Standard Score: The z Score Fat and Skinny Frequency Distributions Summary Time to PracticePART IV • SIGNIFICANTLY DIFFERENT: USING INFERENTIAL STATISTICSChapter 9 • Significantly Significant: What It Means for You and Me The Concept of Significance Significance Versus Meaningfulness An Introduction to Inferential Statistics An Introduction to Tests of Significance Be Even More Confident Summary Time to PracticeChapter 10 • The One-Sample z Test: Only the Lonely Introduction to the One-Sample z Test The Path to Wisdom and Knowledge Computing the z Test Statistic Using SPSS to Perform a z Test Special Effects: Are Those Differences for Real? Summary Time to PracticeChapter 11 • t(ea) for Two: Tests Between the Means of Different Groups Introduction to the t Test for Independent Samples The Path to Wisdom and Knowledge Computing the t Test Statistic The Effect Size and t(ea) for Two Using SPSS to Perform a t Test Summary Time to PracticeChapter 12 • t(ea) for Two (Again): Tests Between the Means of Related Groups Introduction to the t Test for Dependent Samples The Path to Wisdom and Knowledge Computing the t Test Statistic Using SPSS to Perform a Dependent t Test The Effect Size for t(ea) for Two (Again) Summary Time to PracticeChapter 13 • Two Groups Too Many? Try Analysis of Variance Introduction to Analysis of Variance The Path to Wisdom and Knowledge Different Flavors of Analysis of Variance Computing the F Test Statistic Using SPSS to Compute the F Ratio The Effect Size for One-Way ANOVA Summary Time to PracticeChapter 14 • Two Too Many Factors: Factorial Analysis of VarianceA Brief Introduction Introduction to Factorial Analysis of Variance The Path to Wisdom and Knowledge A New Flavor of ANOVA The Main Event: Main Effects in Factorial ANOVA Even More Interesting: Interaction Effects Using SPSS to Compute the F Ratio Computing the Effect Size for Factorial ANOVA Summary Time to PracticeChapter 15 • Testing Relationships Using the Correlation Coefficient: Cousins or Just Good Friends? Introduction to Testing the Correlation Coefficient The Path to Wisdom and Knowledge Computing the Test Statistic Using SPSS to Compute a Correlation Coefficient (Again) Summary Time to PracticeChapter 16 • Using Linear Regression: Predicting the Future Introduction to Linear Regression What Is Prediction All About? The Logic of Prediction Drawing the World’s Best Line (for Your Data) How Good Is Your Prediction? Using SPSS to Compute the Regression Line The More Predictors the Better? Maybe Summary Time to PracticePART V • MORE STATISTICS! MORE TOOLS! MORE FUN!Chapter 17 • Chi-Square and Some Other Nonparametric Tests: What to Do When You’re Not Normal Introduction to Nonparametric Statistics Introduction to the Goodness-of-Fit (One-Sample) Chi-Square Computing the Goodness-of-Fit Chi-Square Test Statistic Introduction to the Test of Independence Chi-Square Computing the Test of Independence Chi-Square Test Statistic Using SPSS to Perform Chi-Square Tests Other Nonparametric Tests You Should Know About Summary Time to PracticeChapter 18 • Some Other (Important) Statistical Procedures You Should Know About Multivariate Analysis of Variance Repeated-Measures Analysis of Variance Analysis of Covariance Multiple Regression Meta-Analysis Discriminant Analysis Factor Analysis Path Analysis Structural Equation Modeling SummaryChapter 19 • Data Mining: An Introduction to Getting the Most Out of Your BIG Data Our Sample Data SetWho Doesn’t Love Babies? Counting Outcomes Pivot Tables and Cross-Tabulation: Finding Hidden Patterns Summary Time to PracticeAppendix A: SPSS Statistics in Less Than 30 MinutesAppendix B: TablesAppendix C: Data SetsAppendix D: Answers to Practice QuestionsAppendix E: Math: Just the BasicsAppendix F: A Statistical Software SamplerAppendix G: The 10 (or More) Best (and Most Fun) Internet Sites for Statistics StuffAppendix H: The 10 Commandments of Data CollectionAppendix I: The Reward: The Brownie RecipeGlossaryIndex