Student Friendly Statistics

PREFACE TO THE INSTRUCTOR The purpose of this text is to make the major statistics accessible to all students while revealing the depth of the statistics and their meaning within research design. The statistics are explained completely, with simple terms and an interactive style. The main statistics concepts treated are the logic of statistical inference, thet-test, single-factor and multifactor analysis of variance (including interaction), linear regression and correlation, and chi-square. Because the tools of ANOVA, interaction, and correlation/regression are extremely important; I provide a foundation for them in the first parts of the book that is solid yet brief enough to allow major coverage of these advanced statistics in a semester course. Relations to experimental design are covered in order to increase the meaningfulness of statistics. Any instructor knows that consistent effort is needed to learn statistics and to individuate them from each other. To get this idea across, I have developed the mountain-climbing journey metaphor illustrated. Each statistic is pictured as a mountain that can be unpacked into more basic concepts. The hikers represent student progress along the journey. A pair of hikers indicates the student's position as each chapter begins, and the spacing between hikers corresponds to chapter length. Initial chapters are short and easy for a gradual warm-up, followed by longer chapters as the material becomes more advanced. The journey metaphor also helps students learn to individuate statistics, an issue that is emphasized in the last chapter, as students look back at their path and the differences between statistics. The exposition of the statistics is motivated by the psychologies of perception, cognition, and learning. The goal is to help students establish a core understanding that will be maintained in memory. All statistics are taught in the context of tables that break the computations into meaningful pieces. Page layouts are designed to group related ideas and figures, and to facilitate student interaction. Definitional formulas are used because they are meaningful; opaque computational formulas are eschewed because they are unnecessary in this age of computers. Major ideas common to most statistics are reinforced throughout the book. Because context aids learning, the statistics are presented within meaningful research contexts. To simplify exposition, the most prototypical forms of statistics are emphasized. Other important distinctions are covered, but after the main exposition. Active learning is encouraged throughout. You are invited to have students copy activity pages and hand them in for checking. Encourage students to copy formulas and tables on their own paper (the tight spacing of this text was dictated by economics). Overheads can be found at the Internet address that follows. This book is designed to be covered sequentially. However, it is possible to omit any of the more advanced chapters without loss of continuity. (These are Chapters 9 and 10 on multilevel and multifactor ANOVA, respectively, Chapter 11 on regression and correlation, and Chapter 12 on chi-square). I thank the many students who have found statistics rewarding to learn. And I am happy to acknowledge the helpful comments and advice on this text from Madeline Altabe, Judy Bourgeois-Smith, Jacquelyn Fresenius, Jennifer Kisamore, Evelyn Mott, and Doug Rohrer. I am deeply indebted to Tracy Krueger and Jennifer Perone for writing the Exercises. And I thank Allison Westlake for finding a great cover, and Anne Mattson and the PRD Group for being so helpful in the production of this book. I am sure students will find that I've made some small errors, but (hopefully!) no large ones. I invite reports of errors and will post corrections as well as thanks, at http://chuma.cas.usf.educ/~sanockil/SFS_corrections.html. Also, look for overheads, larger versions of the sSanocki, Thomas is the author of 'Student Friendly Statistics', published 2000 under ISBN 9780130265210 and ISBN 0130265217.