Introduction to Probability Theory and Statistical Inference

by Harold J. Larson

Discusses probability theory and to many methods used in problems of statistical inference. The Third Edition features material on descriptive statistics. Cramer-Rao bounds for variance of estimators, two-sample inference procedures, bivariate normal probability law, F-Distribution, and the analysis of variance and non-parametric procedures. Contains numerous practical examples and exercises.

Genres: Mathematics

651 pages, Paperback

First published June 1, 1969

Reviews

[Isen · Rating 3 out of 5]

The first part of the book, dealing with probability theory, is great. The subjects are intuitively motivated and coupled with a generous amount of examples and exercises (which even have solutions!) -- this is of course critical as mathematics is very much learning by doing.

The statistics part of the book, on the other hand, felt unnecessarily obtuse. In part, of course, there is a very real problem that standard theorems of statistics presuppose a much higher level of mathematics than a typical stats student can be expected to have, and I couldn't tell you of the right way to address that problem. Neither could this book.

[Mona Mahfouz · Rating 4 out of 5]

Great book! I've read Larson's Probability Theory and Statistical Inference in context of my post graduate studies. A great thorough guide through most general concepts that were tackled in the course.