Dynamic Programming and Bayesian Inference: Concepts and Applications
by Mohammad Saber Fallah Nezhad (ed.)
Publisher: InTech 2014
Number of pages: 164
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.
Home page url
Download or read it online for free here:
(multiple PDF files)
by A. M. Mood, F. A. Graybill, D. C. Boes - McGraw-Hill
A self contained introduction to classical statistical theory. The material is suitable for students who have successfully completed a single year's course in calculus with no prior knowledge of statistics or probability. Third revised edition.
by Irving W. Burr - McGraw-Hill
The present book is the outgrowth of a course in statistics for engineers which has been given at Purdue University. The book is written primarily as a text book for junior, senior, and graduate students of engineering and physical science.
by Pete Kaslik
Contents: Statistical Reasoning; Obtaining Useful Evidence; Examining the Evidence Using Graphs and Statistics; Inferential Theory; Testing Hypotheses; Confidence Intervals and Sample Size; Analysis of Bivariate Quantitative Data; Chi Square; etc.
by Walter Antoniotti - 21st Century Learning Products
Walter Antoniotti's book is for people with a limited mathematics background who want to learn the material covered in a traditional college statistics course and for people who want to learn statistics to enhance their career.