by James E. Gentle
Publisher: Springer 2009
Number of pages: 729
This book describes computationally-intensive statistical methods in a unified presentation, emphasizing techniques, such as the PDF decomposition, that arise in a wide range of methods. The book assumes an intermediate background in mathematics, computing, and applied and theoretical statistics.
Home page url
Download or read it online for free here:
(multiple PDF files)
by Daniel McFadden - University of California, Berkeley
The contents: Economic Analysis and Econometrics; Analysis and Linear Algebra in a Nutshell; Probability Theory in a Nutshell; Limit Theorems in Statistics; Experiments, Sampling, and Statistical Decisions; Estimation; Hypothesis Testing.
by Allen B. Downey - Green Tea Press
Think Bayes is an introduction to Bayesian statistics using computational methods. Contents: Bayes's Theorem; Computational statistics; Tanks and Trains; Urns and Coins; Odds and addends; Hockey; The variability hypothesis; Hypothesis testing.
by J.K. Lindsey - Hodder Education Publishers
Written by a renowned statistician, this book presents the basic ideas behind the statistical methods commonly used in studies of human subjects. It is an ideal guide for advanced undergraduates who are beginning to do their own research.
by Daniel Navarro - University of Adelaide
This is an introductory statistics textbook pitched primarily at psychology students. It covers the standard topics of such a book: study design, descriptive statistics, the theory of hypothesis testing, t-tests, X2 tests, ANOVA and regression.