A Mathematical Primer for Social Statistics

John Fox received a BA from the City College of New York and a PhD from the University of Michigan, both in Sociology. He is Professor Emeritus of Sociology at McMaster University in Hamilton, Ontario, Canada, where he was previously the Senator William McMaster Professor of Social Statistics. Prior to coming to McMaster, he was Professor of Sociology, Professor of Mathematics and Statistics, and Coordinator of the Statistical Consulting Service at York University in Toronto. Professor Fox is the author of many articles and books on applied statistics, including /emph{Applied Regression Analysis and Generalized Linear Models, Third Edition} (Sage, 2016). He is an elected member of the R Foundation, an associate editor of the Journal of Statistical Software, a prior editor of R News and its successor the R Journal, and a prior editor of the Sage Quantitative Applications in the Social Sciences monograph series.  

About the Author
Series Editor Introduction
Acknowledgments
Preface
Matrices, Linear Algebra, and Vector Geometry: The Basics
Matrix Decompositions and Quadratic Forms
An Introduction to Calculus
Elementary Probability Theory
Common Probability Distributions
An Introduction to Statistical Theory
Putting the Math to Work: Linear Least-Squares Regression
References
Index