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The second edition of Statistics for the Social Sciences prepares students from a wide range of disciplines to interpret and learn the statistical methods critical to their field of study. By using the General Linear Model (GLM), the author builds a foundation that enables students to see how statistical methods are interrelated enabling them to build on the basic skills. The author makes statistics relevant to students' varying majors by using fascinating real-life examples from the social sciences. Students who use this edition will benefit from clear explanations, warnings against common erroneous beliefs about statistics, and the latest developments in the philosophy, reporting, and practice of statistics in the social sciences. The textbook is packed with helpful pedagogical features including learning goals, guided practice, and reflection questions.
List of contents
1. Statistics and Models; 2. Levels of Data; 3. Models of Central Tendency and Variability; 4. Visual Models; 5. Linear Transformations and z-Scores; 6. Probability and the Central Limit Theorem; 7. Null Hypothesis Statistical Significance Testing and z-Tests; 8. One-Sample t-Tests; 9. Paired-Samples t-Tests; 10. Unpaired Two-Sample t-Tests; 11. Analysis of Variance; 12. Correlation; 13. Regression; 14. Chi-Squared Test; 15 Applying Statistics to Research, and Advanced Statistical Methods.
About the author
Russell T. Warne is an associate professor of psychology at Utah Valley University, USA, where he has taught since 2011. He has won awards from the Southwest Educational Research Association, National Association for Gifted Children, and Mensa. He is an associate editor for the Journal for the Education of the Gifted and serves on the editorial boards for Intelligence, the Journal of School Psychology, Gifted Child Quarterly, and the Journal of Psychoeducational Assessment. He is also the author of In the Know: Debunking 35 Myths About Human Intelligence (Cambridge University Press).
Summary
This textbook introduces statistics using the General Linear Model, a method that shows the interconnections among statistical concepts. The second edition is for undergraduate social science majors in a one-semester statistics course and provides timely updates, building on the success of the first edition.
Report
'Dr Warne's gift for teaching statistics is apparent in his writing of this book. Indeed, I wish I had this book when I was a student. His use of the General Linear Model as a schema for understanding how statistical methods are interrelated sets the book apart from others.' Leena J. Landmark, Associate Professor of Special Education, Sam Houston State University, USA
