Lectures on Statistics
by Robert B. Ash
Publisher: University of Illinois 2007
These notes are based on a course that the author gave at UIUC in 1996 and again in 1997. No prior knowledge of statistics is assumed. A standard first course in probability is a prerequisite, but the first 8 lectures review results from basic probability that are important in statistics. Some exposure to matrix algebra is needed to cope with the multivariate normal distribution in Lecture 21, and there is a linear algebra review in Lecture 19.
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by Peter Young - arXiv
These notes discuss, in a style intended for physicists, how to average data and fit it to some functional form. I try to make clear what is being calculated, what assumptions are being made, and to give a derivation of results.
by David W. Stockburger - Missouri State University
The book 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 wrote about mathematical ideas.
by James E. Gentle - George Mason University
This document is directed toward students for whom mathematical statistics is or will become an important part of their lives. Obviously, such students should be able to work through the details of 'hard' proofs and derivations.
by C.E. Weatherburn - Cambridge University Press
This book provides the mathematical foundations of statistics. It explains the principles, and proves the formulae to give validity to the methods of the interpretation of statistical data. It is of interest to students of a wide variety of subjects.