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 Mohammed A. Shayib - Bookboon
The book introduces the concepts, definitions, and terminology of the subject in an elementary presentation with a mathematical background which does not surpass college algebra. It should prepare the reader to make a good decision based on data.
Statistics is used in almost every field of research. We will learn about subjects in modern statistics and some applications of statistics. We will also lay out some of the background mathematical concepts required to begin studying statistics.
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 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.