Statistics for People Who (Think They) Hate Statistics

The bestselling Statistics for People Who (Think They) Hate Statistics teaches an often intimidating and difficult subject in a way that is informative, personable, and clear. In the Eighth Edition, the authors take students through various statistical procedures, beginning with correlation and graphical representation of data and ending with inferential techniques and analysis of variance.

Table of Contents:
A Note to the Student Acknowledgments And Now, About the Eighth Edition … Sage Vantage Features About the Authors Part I: Yippee! I’m in Statistics Chapter 1: Statistics or Sadistics? It’s Up to You Why Statistics? Descriptive Statistics and Averages Computing the Mean Computing the Median Computing the Mode Summary Key Terms Activities Review Questions Critical Thinking Questions Chapter 2: What Do Your Data Look Like? Summarizing and Picturing Distributions How Much Information Is in Your Variable? Vive la Différence! Understanding Variability The Standard Deviation Using SPSS to Compute Descriptive Statistics Shaping Things Up Using the Computer (SPSS, That Is) to Illustrate Data Summary Key Terms Activities Review Questions Critical Thinking Questions Chapter 3: Computing Correlation Coefficients: Ice Cream and Crime How’s Your Relationship? Computing a Pearson Correlation Coefficient What’s It All Mean? Ice Cream Causes Crime (Association vs. Causation) Using SPSS to Compute a Correlation Coefficient Other Cool Correlations Parting Ways: A Bit About Partial Correlations Summary Key Terms Activities Review Questions Critical Thinking Questions Chapter 4: Reliability and Validity: Tell the Truth, Precisely the Truth Reliability: Getting It Right the First Time Different Types of Reliability Internal Consistency Reliability: To One’s Own Self Be True Interrater Reliability: Agreeing Not to Disagree How Big Is Big? Interpreting Reliability Coefficients Validity: What’s the Meaning of Life!? Validity and Reliability: Really Close Cousins Summary Key Terms Activities Review Questions Critical Thinking Questions Part II: Taking Chances for Fun and Profit Chapter 5: The Normal Curve: It′s Shaped Like a Bell and It′s Everywhere! Distributions and Probabilities Area Codes: Areas Under the Normal Curve The Amazing Super-Informative z Score Using SPSS to Compute z Scores Fat and Skinny Frequency Distributions Summary Key Terms Activities Review Questions Critical Thinking Questions Chapter 6: Hypotheticals and You: Making Guesses Samples and Populations The Null Hypothesis The Research Hypothesis What Makes a Good Research Hypothesis? Summary Key Terms Activities Review Questions Critical Thinking Questions Chapter 7: Significance: Not Everything That Can Be Counted Counts The Concept of Significance Significance Versus Meaningfulness An Introduction to Inferential Statistics An Introduction to Tests of Significance Be Even More Confident Summary Key Terms Activities Review Questions Critical Thinking Questions Part III: Significantly Different: Using Inferential Statistics Chapter 8: Single Samples: One Group All Alone Introduction to the Single-Sample z Test Computing the z Test Statistic Using SPSS to Perform a z Test t Test Special Effects: Do They Matter? Summary Key Terms Activities Review Questions Critical Thinking Questions Chapter 9: t(ea) for Two: Comparing Two Means The Classic Group Comparison: Independent t Test The Effect Size for a Two-Group Comparison Using SPSS to Perform an Independent t Test Using SPSS to Perform a Paired-Samples t Test Summary Key Terms Activities Review Questions Critical Thinking Questions Chapter 10: More Than Two Groups?: Analysis of Variance to the Rescue 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 Key Terms Activities Review Questions Critical Thinking Questions Chapter 11: Two (or More) ANOVAs in One: Factorial Analysis of Variance Factorial Analysis of Variance A New Flavor of ANOVA The Main Event: Main Effects in Factorial ANOVA Even More Interesting: Interaction Effects Using SPSS to Conduct a Factorial Analysis of Variance Computing the Effect Size for Factorial ANOVA Summary Key Terms Activities Review Questions Critical Thinking Questions Chapter 12: Correlation Coefficients and Regression: Can You Relate? Remember the Correlation Coefficient? Computing the Test Statistic Linear Regression Drawing the World’s Best Line (for Your Data) How Good Is Your Prediction? Using SPSS to Compute the Regression Line Multiple Regression: The More Predictors the Better? Maybe Summary Key Terms Activities Review Questions Critical Thinking Questions Part IV: More Statistics! More Tools! More Fun! Chapter 13: 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 Chi-Square Test of Independence Using SPSS to Perform Chi-Square Tests Other Nonparametric Tests You Should Know About Summary Key Terms Activities Review Questions Critical Thinking Questions Chapter 14: Some Other (Important) Statistical Stuff You Should Know About Sophisticated Group Comparisons Sophisticated Correlational Analyses It’s Not about What Data is Mine, it’s about What Data is Mined Using Chatbots for Statistical Analyses Summary Key Terms Appendices: Information Never Ends! Appendix A: SPSS Statistics in Less Than 30 Minutes Appendix B: Tables Appendix C: Data Sets Appendix D: Answers to Practice Questions Appendix E: Math: Just the Basics Appendix F: The 10 Commandments of Data Collection Appendix G: The Reward Glossary

About the Author :
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.

Review :
Of all the statistics textbooks that I have reviewed, Statistics for People Who (Think They) Hate Statistics is by far the best. [Statistics for People Who (Think They) Hate Statistics] eases students into concepts with clear intention for each chapter and prompts them to connect everything they′ve learned. Two of my favorite statistical authors being together in one book may be a dream come true. Both Salkind′s and Frey′s texts have been a survival manual both for me and for my students. There are very few texts that carry both the weight of statistical grandeur along with the depth of content like this new text does. This is a masterpiece of statistical reference data that meshes the best parts of both authors and fills in the gap following the passing of Salkind. I can′t wait to get this new text into the hands of my students, and I know that this new book is going to become a foundational pillar in all of my classes. This book has a successful conversion mission. Indeed, it succeeds in converting statistics-shy students into statistics-savvy ardent learners. The re-appearance of this mind-catching treasure is a major plus in the effective teaching and easy learning of an introductory course in descriptive and inferential statistics. Salkind and Frey have written an informative and comprehensive text for the introductory statistics course that is also funny and disarming. My graduate students —many of whom exhibit an initial wariness toward math courses and long-dormant math skills—have found it to be an unexpected pleasure and an accessible read. Many students appear unaware that they are using statistics and research methods in their daily lives. When I mention statistics in the research methods course, some get very anxious and remind me that they are not "math people". Statistics for People Who (Think They) Hate Statistics is a helpful supplemental text for a research methods course. It provides a different perspective regarding how statistics are used and helps students retrieve and build on their statistics knowledge. The text uses humor and interesting examples and helps illustrate why certain research issues are important. I love the layout of the text and the detailed and straightforward explanations of many of the concepts that students often struggle to comprehend when it comes to statistics. The authors′ introduction of SPSS and their step-by-step instructions for its use was superior to any other texts that I considered.