Applied Multivariate Statistical Analysis
by Wolfgang K. Hardle, Leopold Simar
Publisher: Springer 2003
Number of pages: 488
The authors' intention is to present multivariate data analysis in a way that is understandable to non-mathematicians and practitioners who are confronted by statistical data analysis. The book has a friendly yet rigorous style. All methods are demonstrated through numerous real examples. Mathematical results are clearly stated.
Download or read it online for free here:
by Hugh D. Young - McGraw Hill
A concise, highly readable introduction to statistical methods. Even with a limited mathematics background, readers can understand what statistical methods are and how they may be used to obtain the best possible results from experimental data.
by Denis Anthony - BookBoon
This is a practical book. It is aimed at people who need to understand statistics, but not develop it as a subject. The typical reader might be a postgraduate student in health, life, or social science who has no knowledge of statistics.
by Ryan Martin - University of Illinois at Chicago
Table of contents: Statistics and Sampling Distributions; Point Estimation Basics; Likelihood and Maximum Likelihood Estimation; Sufficiency and Minimum Variance Estimation; Hypothesis Testing; Bayesian Statistic; What Else is There to Learn?
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.