Study Guide to Accompany Neil J. Salkind's Statistics for People Who (Think They) Hate Statistics / Edition 5 available in Paperback
The Study Guide to Accompany Neil J. Salkind's Statistics for People Who (Think They) Hate Statistics, Sixth Edition includes chapter outlines; chapter summaries; learning objectives; key terms; exercises; true/false, multiple choice, and essay questions; as well as answers to all questions. The guide has been updated to match the organization of Salkind’s text and includes activities for the book's new Chapter 19: Data Mining: An Introduction to Getting the Most Out of Your BIG Data.
|Edition description:||Fifth Edition|
|Product dimensions:||8.50(w) x 10.80(h) x 0.50(d)|
About the Author
Neil J. Salkind received his PhD from the University of Maryland in Human Development, and taught for 35 years at the University of Kansas in the Department of Psychology and Research in Education. 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 and the focus was 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; and wrote 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 edited several encyclopedias, including the Encyclopedia of Human Development, the Encyclopedia of Measurement and Statistics, and the recently published Encyclopedia of Research Design. He was editor of Child Development Abstracts and Bibliography for 13 years.
Table of ContentsChapter 1: Statistics or Sadistics? It’s Up to YouChapter 2: Means to an End: Computing and Understanding AveragesChapter 3: Vive la Différence: Understanding VariabilityChapter 4: A Picture Really Is Worth a Thousand WordsChapter 5: Ice Cream and Crime: Computing Correlation CoefficientsChapter 6: Just the Truth: An Introduction to Understanding Reliability and ValidityChapter 7: Hypotheticals and You: Testing Your QuestionsChapter 8: Are Your Curves Normal? Probability and Why It CountsChapter 9: Significantly Significant: What It Means for You and MeChapter 10: Only the Lonely: The One-Sample z-TestChapter 11: t(ea) for Two: Tests Between the Means of Different GroupsChapter 12: t(ea) for Two (Again): Tests Between the Means of Related GroupsChapter 13: Two Groups Too Many? Try Analysis of VarianceChapter 14: Two Too Many Factors: Factorial Analysis of Variance: A Brief IntroductionChapter 15: Cousins or Just Good Friends? Testing Relationships Using the Correlation CoefficientChapter 16: Predicting Who’ll Win the Super Bowl: Using Linear RegressionChapter 17: What to Do When You’re Not Normal: Chi-Square and Some Other Nonparametric TestsChapter 18: Some Other (Important) Statistical Procedures You Should Know AboutChapter 19: Data Mining: An Introduction to Getting the Most Out of Your BIG Data