Statistics for the Social Sciences (2nd Edition)

A General Linear Model Approach

Statistics for the Social Sciences  (2nd Edition)
Russell T Warne
RRP:
NZ$ 118.95
Our Price:
NZ$ 107.05
Paperback
h259 x 203mm - 650pg
17 Dec 2020 UK
International import eta 7-19 days
9781108814508
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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.
' 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
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).

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