Statistics for People Who (Think They) Hate Statistics - International Student Edition

Neil J. Salkind received his PhD 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, PhD, is an award-winning researcher, author, teacher, and professor of educational psychology at the University of Kansas. He is the editor of The SAGE Encyclopedia of Educational Research, Measurement and Evaluation and the SAGE Encyclopedia of Educational Design. In addition to being the lead author for The Statistics for People Who (Think They) Hate Statistics series, his books for Sage include There’s a Stat for That!, and 100 Questions (and Answers) About Tests and Measurement. He also wrote Statistics Hacks for O’Reilly Media. In his spare time, Bruce leads a secret life as Professor Bubblegum, host of a YouTube channel and Echo Valley, a podcast that celebrates bubblegum pop music of the late 1960s. The show is wildly popular with the young people.

Perfect for my many students who Who (Think They) Hate Statistics

• A Note to the Student: Why We Wrote This BookAcknowledgementsAnd Now, About the Seventh EditionAbout the AuthorsPart I: Yippee! I′m in Statistics!Chapter 1. Statistics or Sadistics? It’s Up to YouWhat You Will Learn in This ChapterWhy Statistics?A 5-Minute History of StatisticsStatistics: 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 FeaturesKey to Difficulty IconsGlossarySummaryPart II: Zigma Freud and Descriptive StatisticsChapter 2. Computing and Understanding Averages: Means to an EndWhat You Will Learn in This ChapterComputing the MeanComputing the MedianComputing the ModeWhen to Use What Measure of Central Tendency (and All You Need to Know About Scales of Measurement for Now)Using SPSS to Compute Descriptive StatisticsReal-World StatsSummaryTime to PracticeChapter 3. Understanding Variability: Vivé la DifférenceWhat You Will Learn in This ChapterWhy Understanding Variability Is ImportantComputing the RangeComputing the Standard DeviationComputing the VarianceUsing SPSS to Compute Measures of VariabilityReal-World StatsSummaryTime to PracticeChapter 4. Creating Graphs: A Picture Really Is Worth a Thousand WordsWhat You Will Learn in This ChapterWhy Illustrate Data?Ten Ways to a Great Figure (Eat Less and Exercise More?)First Things First: Creating a Frequency DistributionThe Plot Thickens: Creating a HistogramThe Next Step: A Frequency PolygonOther Cool Ways to Chart DataUsing the Computer (SPSS, That Is) to Illustrate DataReal-World StatsSummaryTime to PracticeChapter 5. Computing Correlation Coefficients: Ice Cream and CrimeWhat You Will Learn in This ChapterWhat Are Correlations All About?Computing a Simple Correlation CoefficientUnderstanding What the Correlation Coefficient MeansSquaring the Correlation Coefficient: A Determined EffortOther Cool CorrelationsParting Ways: A Bit About Partial CorrelationReal-World StatsSummaryTime to PracticeChapter 6. An Introduction to Understanding Reliability and Validity: Just the TruthWhat You Will Learn in This ChapterAn Introduction to Reliability and ValidityReliability: Doing It Again Until You Get It RightDifferent Types of ReliabilityHow Big Is Big? Finally: Interpreting Reliability CoefficientsValidity: Whoa! What Is the Truth?A Last Friendly WordValidity and Reliability: Really Close CousinsReal-World StatsSummaryTime to PracticePart III: Taking Chances for Fun and ProfitChapter 7. Hypotheticals and You: Testing Your QuestionsWhat You Will Learn in This ChapterSo You Want to Be a Scientist?.?.?.Samples and PopulationsThe Null HypothesisThe Research HypothesisWhat Makes a Good Hypothesis?Real-World StatsSummaryTime to PracticeChapter 8. Probability and Why it Counts: Fun with a Bell-Shaped CurveWhat You Will Learn in This ChapterWhy Probability?The Normal Curve (a.k.a. the Bell-Shaped Curve)Our Favorite Standard Score: The z ScoreFat and Skinny Frequency DistributionsReal-World StatsSummaryTime to PracticePart IV Significantly Different: Using Inferential StatisticsChapter 9. Significantly Significant: What It Means for You and MeWhat You Will Learn in This ChapterThe Concept of SignificanceSignificance Versus MeaningfulnessAn Introduction to Inferential StatisticsAn Introduction to Tests of SignificanceBe Even More ConfidentReal-World StatsSummaryTime to PracticeChapter 10. The One-Sample Z Test: Only the LonelyWhat You Will Learn in This ChapterIntroduction to the One-Sample Z TestThe Path to Wisdom and KnowledgeComputing the Z Test StatisticUsing SPSS to Perform a Z TestSpecial Effects: Are Those Differences for Real?Real-World StatsSummaryTime to PracticeChapter 11. t(ea) for Two: Tests Between the Means of Different GroupsWhat You Will Learn in This ChapterIntroduction to the t Test for Independent SamplesThe Path to Wisdom and KnowledgeComputing the t Test StatisticThe Effect Size and t(ea) for TwoUsing SPSS to Perform a t TestReal-World StatsSummaryTime to PracticeChapter 12. t(ea) for Two (Again): Tests Between the Means of Related GroupsWhat You Will Learn in This ChapterIntroduction to the t Test for Dependent SamplesThe Path to Wisdom and KnowledgeComputing the t Test StatisticUsing SPSS to Perform a Dependent t TestThe Effect Size for t(ea) for Two (Again)Real-World StatsSummaryTime to PracticeChapter 13. Two Groups Too Many? Try Analysis of VarianceWhat You Will Learn in This ChapterIntroduction to Analysis of VarianceThe Path to Wisdom and KnowledgeDifferent Flavors of Analysis of VarianceComputing the F Test StatisticUsing SPSS to Compute the F RatioThe Effect Size for One-Way ANOVAReal World StatsSummaryTime to PracticeChapter 14. Two Too Many Factors: Factorial Analysis of Variance—A Brief IntroductionWhat You Will Learn in This ChapterIntroduction to Factorial Analysis of VarianceThe Path to Wisdom and KnowledgeA New Flavor of ANOVAThe Main Event: Main Effects in Factorial ANOVAEven More Interesting: Interaction EffectsUsing SPSS to Compute the F RatioComputing the Effect Size for Factorial ANOVAReal World StatsSummaryTime to PracticeChapter 15. Testing Relationships Using the Correlation Coefficient: Cousins or Just Good Friends?What You Will Learn in This ChapterIntroduction to Testing the Correlation CoefficientThe Path to Wisdom and KnowledgeComputing the Test StatisticUsing SPSS to Compute a Correlation Coefficient (Again)Real World StatsSummaryTime to PracticeChapter 16. Using Linear Regression: Predicting the FutureWhat You Will Learn in This ChapterIntroduction to Linear RegressionWhat Is Prediction All About?The Logic of PredictionDrawing the World’s Best Line (for Your Data)How Good Is Your Prediction?Using SPSS to Compute the Regression LineThe More Predictors the Better? MaybeReal-World StatsSummaryTime 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 NormalWhat You Will Learn in This ChapterIntroduction to Nonparametric StatisticsIntroduction to the Goodness of Fit (One-Sample) Chi-SquareComputing the Goodness of Fit Chi-Square Test StatisticIntroduction to the Test of Independence Chi-SquareComputing the Test of Independence Chi-Square Test StatisticUsing SPSS to Perform Chi-Square TestsOther Nonparametric Tests You Should Know AboutReal-World StatsSummaryTime to PracticeChapter 18. Some Other (Important) Statistical Procedures You Should Know AboutWhat You Will Learn in This ChapterMultivariate Analysis of VarianceRepeated Measures Analysis of VarianceAnalysis of CovarianceMultiple RegressionMeta-analysisDiscriminant AnalysisFactor AnalysisPath AnalysisStructural Equation ModelingSummaryChapter 19. Data Mining: An Introduction to Getting the Most Out of Your BIG DataWhat You Will Learn in This ChapterOur Sample Data Set—Who Doesn’t Love Babies?Counting OutcomesPivot Tables and Cross-Tabulation: Finding Hidden PatternsSummaryTime to PracticeAppendix AAppendix BAppendix CAppendix DAppendix EAppendix FAppendix GAppendix HAppendix IGlossary