Statistics for People Who (Think They) Hate Statistics

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.

Of all the statistics textbooks that I have reviewed, Statistics for People Who (Think They) Hate Statistics is by far the best.

• A Note to the StudentAcknowledgmentsAnd Now, About the Eighth Edition …Sage Vantage FeaturesAbout the AuthorsPart I: Yippee! I’m in StatisticsChapter 1: Statistics or Sadistics? It’s Up to YouWhy Statistics?Descriptive Statistics and AveragesComputing the MeanComputing the MedianComputing the ModeSummaryKey TermsActivitiesReview QuestionsCritical Thinking QuestionsChapter 2: What Do Your Data Look Like? Summarizing and Picturing DistributionsHow Much Information Is in Your Variable?Vive la Différence! Understanding VariabilityThe Standard DeviationUsing SPSS to Compute Descriptive StatisticsShaping Things UpUsing the Computer (SPSS, That Is) to Illustrate DataSummaryKey TermsActivitiesReview QuestionsCritical Thinking QuestionsChapter 3: Computing Correlation Coefficients: Ice Cream and CrimeHow’s Your Relationship?Computing a Pearson Correlation CoefficientWhat’s It All Mean?Ice Cream Causes Crime (Association vs. Causation)Using SPSS to Compute a Correlation CoefficientOther Cool CorrelationsParting Ways: A Bit About Partial CorrelationsSummaryKey TermsActivitiesReview QuestionsCritical Thinking QuestionsChapter 4: Reliability and Validity: Tell the Truth, Precisely the TruthReliability: Getting It Right the First TimeDifferent Types of ReliabilityInternal Consistency Reliability: To One’s Own Self Be TrueInterrater Reliability: Agreeing Not to DisagreeHow Big Is Big? Interpreting Reliability CoefficientsValidity: What’s the Meaning of Life!?Validity and Reliability: Really Close CousinsSummaryKey TermsActivitiesReview QuestionsCritical Thinking QuestionsPart II: Taking Chances for Fun and ProfitChapter 5: The Normal Curve: It′s Shaped Like a Bell and It′s Everywhere!Distributions and ProbabilitiesArea Codes: Areas Under the Normal CurveThe Amazing Super-Informative z ScoreUsing SPSS to Compute z ScoresFat and Skinny Frequency DistributionsSummaryKey TermsActivitiesReview QuestionsCritical Thinking QuestionsChapter 6: Hypotheticals and You: Making GuessesSamples and PopulationsThe Null HypothesisThe Research HypothesisWhat Makes a Good Research Hypothesis?SummaryKey TermsActivitiesReview QuestionsCritical Thinking QuestionsChapter 7: Significance: Not Everything That Can Be Counted CountsThe Concept of SignificanceSignificance Versus MeaningfulnessAn Introduction to Inferential StatisticsAn Introduction to Tests of SignificanceBe Even More ConfidentSummaryKey TermsActivitiesReview QuestionsCritical Thinking QuestionsPart III: Significantly Different: Using Inferential StatisticsChapter 8: Single Samples: One Group All AloneIntroduction to the Single-Sample z TestComputing the z Test StatisticUsing SPSS to Perform a z Test t TestSpecial Effects: Do They Matter?SummaryKey TermsActivitiesReview QuestionsCritical Thinking QuestionsChapter 9: t(ea) for Two: Comparing Two MeansThe Classic Group Comparison: Independent t TestThe Effect Size for a Two-Group ComparisonUsing SPSS to Perform an Independent t TestUsing SPSS to Perform a Paired-Samples t TestSummaryKey TermsActivitiesReview QuestionsCritical Thinking QuestionsChapter 10: More Than Two Groups?: Analysis of Variance to the RescueDifferent Flavors of Analysis of VarianceComputing the F Test StatisticUsing SPSS to Compute the F RatioThe Effect Size for One-Way ANOVASummaryKey TermsActivitiesReview QuestionsCritical Thinking QuestionsChapter 11: Two (or More) ANOVAs in One: Factorial Analysis of VarianceFactorial Analysis of VarianceA New Flavor of ANOVAThe Main Event: Main Effects in Factorial ANOVAEven More Interesting: Interaction EffectsUsing SPSS to Conduct a Factorial Analysis of VarianceComputing the Effect Size for Factorial ANOVASummaryKey TermsActivitiesReview QuestionsCritical Thinking QuestionsChapter 12: Correlation Coefficients and Regression: Can You Relate?Remember the Correlation Coefficient?Computing the Test StatisticLinear RegressionDrawing the World’s Best Line (for Your Data)How Good Is Your Prediction?Using SPSS to Compute the Regression LineMultiple Regression: The More Predictors the Better? MaybeSummaryKey TermsActivitiesReview QuestionsCritical Thinking QuestionsPart IV: More Statistics! More Tools! More Fun!Chapter 13: Chi-Square and Some Other Nonparametric Tests: What to Do When You′re Not NormalIntroduction to Nonparametric StatisticsIntroduction to the Goodness-of-Fit (One-Sample) Chi-SquareComputing the Goodness-of-Fit Chi-Square Test StatisticIntroduction to the Chi-Square Test of IndependenceUsing SPSS to Perform Chi-Square TestsOther Nonparametric Tests You Should Know AboutSummaryKey TermsActivitiesReview QuestionsCritical Thinking QuestionsChapter 14: Some Other (Important) Statistical Stuff You Should Know AboutSophisticated Group ComparisonsSophisticated Correlational AnalysesIt’s Not about What Data is Mine, it’s about What Data is MinedUsing Chatbots for Statistical AnalysesSummaryKey TermsAppendices: Information Never Ends!Appendix A: SPSS Statistics in Less Than 30 MinutesAppendix B: TablesAppendix C: Data SetsAppendix D: Answers to Practice QuestionsAppendix E: Math: Just the BasicsAppendix F: The 10 Commandments of Data CollectionAppendix G: The RewardGlossary