A Mathematical Primer for Social Statistics, Second Edition presents mathematics central to learning and understanding statistical methods beyond the introductory level: the basic "language" of matrices and linear algebra and its visual representation, vector geometry; differential and integral calculus; probability theory; common probability distributions; statistical estimation and inference, including likelihood-based and Bayesian methods. The volume concludes by applying mathematical concepts and operations to a familiar case, linear least-squares regression. The Second Edition pays more attention to visualization, including the elliptical geometry of quadratic forms and its application to statistics. It also covers some new topics, such as an introduction to Markov-Chain Monte Carlo methods, which are important in modern Bayesian statistics. A companion website includes materials that enable readers to use the R statistical computing environment to reproduce and explore computations and visualizations presented in the text. The book is an excellent companion to a "math camp" or a course designed to provide foundational mathematics needed to understand relatively advanced statistical methods.
A Mathematical Primer for Social Statistics Second Edition
In this course, you will learn about probability functions and Bayes' rule (Chapter 3) as well as hypothesis tests such as the student's t, z, F, and χ2 tests. These tests are are built on probability density functions (PDFs) (Section ...
"Presenting topics in the form of questions and answers, this popular supplemental text offers a brief introduction on multiple regression on a conceptual level.
Although the text is largely accessible to readers with a modest background in statistics and mathematics, author John Fox also presents more advanced material in optional sections and chapters throughout the book.
This is a broad introduction to the R statistical computing environment in the context of applied regression analysis.
In simple, non-technical language, this volume explores the fundamentals governing chance and applies them to sports, government, and business.
The book begins with the fundamental building blocks of mathematics and basic algebra, then goes on to cover essential subjects such as calculus in one and more than one variable, including optimization, constrained optimization, and ...
This book is specially designed to refresh and elevate the level of understanding of the foundational background in probability and distributional theory required to be successful in a graduate-level statistics program.
A Cumberland Vendetta is a fictional novel written by John Fox, Jr. The novel is set in Appalachia at the turn of the 20th century.
This 2006 book addresses the comprehensive introduction to the mathematical principles needed by modern social scientists.