Probability and statistics by example. V.1. Basic probability and statistics

✍ Scribed by Yu M Suhov; Michael Kelbert

Publisher: Cambridge University Press
Year: 2005
Tongue: English
Leaves: 374
Series: Probability and statistics.; Probability and statistics, segment 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

This detailed introduction to distribution theory is designed as a text for the probability portion of the first year statistical theory sequence for Master's and PhD students in statistics, biostatistics, and econometrics. The text uses no measure theory, requiring only a background in calculus and linear algebra. Topics range from the basic distribution and density functions, expectation, conditioning, characteristic functions, cumulants, convergence in distribution and the central limit theorem to more advanced concepts such as exchangeability, models with a group structure, asymptotic approximations to integrals and orthogonal polynomials. An appendix gives a detailed summary of the mathematical definitions and results that are used in the book Vol. 1. Basic probability and statistics -- v. 2. Markov chains : a primer in random processes and their applications

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