This is a list of important publications in statistics, organized by field.

Some reasons why a particular publication might be regarded as important:

• Topic creator - A publication that created a new topic
• Breakthrough - A publication that changed scientific knowledge significantly
• Introduction - A publication that is a good introduction or survey of a topic
• Impact - A publication which had a major impact on the world or on the research
• Latest and greatest - The current most advanced result in a topic

Contents

1 Probability 2 Bayesian statistics 3 Applied statistics 4 Analysis of variance 5 Extreme value theory 6 Regression analysis 7 Machine learning 8 Multivariate statistics 9 Statistical phenomena

Probability

The Doctrine of Chances

Author: Abraham de Moivre

Publication data: 1738 (2nd ed.)

Online version: ?

Description: The book introduced the concept of normal distributions as approximations to binomial distributions. In effect, de Moivre proved a weak version of the central limit theorem. Sometimes his result is called the theorem of de Moivre-Laplace.

Importance: Topic creator, Breakthrough, Impact

Bayesian statistics

An Essay Toward Solving a Problem in the Doctrine of Chances

Author: Thomas Bayes

Publication data: 1764

Online version: [1] (PostScript file); [2] (PDF file)

Description: In this paper Bayes addresses the problem of using a sequence of identical "trials" to determine the per-trial probability of "success" — the so-called inverse probability problem. It later inspired the theorem that bears his name (Bayes' theorem). See also Pierre Simon de Laplace.

Importance: Topic creator, Breakthrough, Impact

Applied statistics

Analysis of variance

Extreme value theory

Regression analysis

Machine learning

Multivariate statistics

Statistical phenomena