Logo

A First Course In Mathematical Statistics

Large book cover: A First Course In Mathematical Statistics

A First Course In Mathematical Statistics
by

Publisher: Cambridge University Press
ISBN/ASIN: 0521091586
Number of pages: 302

Description:
This book provides the mathematical foundations of statistics. Its aim is to explain the principles, to prove the formulae to give validity to the methods employed in the interpretation of statistical data. Many examples are included but, since the primary emphasis is on the underlying theory, it is of interest to students of a wide variety of subjects.

Home page url

Download or read it online for free here:
Download link
(multiple formats)

Similar books

Book cover: Statistics Beyond the Absolute BasicsStatistics Beyond the Absolute Basics
by - scientificlanguage.com
The book begins by expanding on some of the basic concepts such data types and variables. The basic choice then is between the family of statistics which compares groups, and the family which studies associations or correlations.
(6380 views)
Book cover: Everything you wanted to know about Data Analysis and FittingEverything you wanted to know about Data Analysis and Fitting
by - 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.
(9750 views)
Book cover: Stats without TearsStats without Tears
by - BrownMath.com
This book is an alternative to the usual textbooks for a one-semester course in statistics. The author tried to make statistics approachable to anyone with high-school math, but it's still a technical subject. There is very little use of formulas.
(7406 views)
Book cover: Computer Age Statistical Inference: Algorithms, Evidence, and Data ScienceComputer Age Statistical Inference: Algorithms, Evidence, and Data Science
by - Stanford University
Beginning with classical inferential theories, the book takes up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, etc.
(4993 views)