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 Jamie DeCoster - University of Alabama
It is important to know how to understand statistics so that we can make the proper judgments when a person presents us with an argument backed by data. Data are numbers with a context. We must always keep the meaning of our data in mind.
by D Caradog Jones - G Bell
First part of the book is within the understanding of the ordinary person. Part 2 is more mathematical, but the results are explained in such a way that the reader shall gain a general idea of the theory and applications without mastering the proofs.
by Mohammad Saber Fallah Nezhad (ed.) - InTech
Dynamic programming and Bayesian inference have been both intensively and extensively developed during recent years. The purpose of this volume is to provide some applications of Bayesian optimization and dynamic programming.
by Henk van Elst - arXiv
These lecture notes were written to provide an accessible though technically solid introduction to the logic of systematical analyses of statistical data to undergraduate and postgraduate students in the Social Sciences and Economics in particular.