Multivariate Statistics: Concepts, Models, and Applications
by David W. Stockburger
Publisher: Missouri State University 2001
The book is designed for a course in multivariate statistics for first year graduate or advanced undergraduates. It is neither a mathematical treatise nor a cookbook. Instead of complicated mathematical proofs the author have attempted to write a book about mathematical ideas.
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by Stan Brown - BrownMath.com
This book is an alternative to the usual textbooks for a one-semester course in statistics. The author tried to make statistics approachable to anyone with high-school math, but it's still a technical subject. There is very little use of formulas.
by Wolfgang K. Hardle, Leopold Simar - Springer
The authors present multivariate data analysis in a way that is understandable to non-mathematicians and practitioners confronted by statistical data analysis. The book has a friendly yet rigorous style. Mathematical results are clearly stated.
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 Christian Akrong Hesse - ResearchGate GmbH
The purpose of this book is to acquaint the reader with the increasing number of applications of statistics in engineering and the applied sciences. Our goal is to introduce the basic theory without getting too involved in mathematical detail.