The Azimuth Project
Mathematical statistics (Rev #4, changes)

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Contents

Idea

Mathematical statistics is about data analysis using different tools from mathematics like probability theory. The analyzed data is often assumed to exhibit some influence from Random processes.

Azimuth will concentrate on the use of mathematical statistics in Earth sciences and Climate models, as a tool to enable an objective assessment of measurements, experiments and models.

References

General

Mathematical statistics is a huge subject, and there is a multiplicity of textbooks. Any recommendation is therefore to be considered to be an example only.

  • Jun Shao: Mathematical statistics. (ZMATH)
  • E.T. Jaynes and G. Larry Bretthorst, Probability Theory: The Logic of Science
  • James Clark: Models For Ecological Data: An Introduction
  • Andrew Gelman, John Carlin, Hal Stern, Donald Rubin: Bayesian Data Analysis
  • Devinderjit Sivia and John Skilling: Data Analysis: A Bayesian Tutorial
  • Giulio D’Agostini: Bayesian Reasoning in Data Analysis
  • Peter Congdon: Bayesian Statistical Modelling

Software

See R.