
Introduction to Randomness and Statistics
by Alexander K. Hartmann
Publisher: arXiv 2009
Number of pages: 95
Description:
This text provides a practical introduction to randomness and data analysis, in particular in the context of computer simulations. At the beginning, the most basics concepts of probability are given, in particular discrete and continuous random variables. The text is basically self-contained, comes with several example C programs and contains eight practical exercises.
Download or read it online for free here:
Download link
(2.4MB, PDF)
Similar books
Bayesian Spectrum Analysis and Parameter Estimationby G. Larry Bretthorst - Springer
This work is a research document on the application of probability theory to the parameter estimation problem. The people who will be interested in this material are physicists, economists, and engineers who have to deal with data on a daily basis.
(21265 views)
Lectures on Stochastic Analysisby Thomas G. Kurtz - University of Wisconsin
Covered topics: stochastic integrals with respect to general semimartingales, stochastic differential equations based on these integrals, integration with respect to Poisson measures, stochastic differential equations for general Markov processes.
(16950 views)
Applied Nonparametric Regressionby Wolfgang Härdle - Cambridge University Press
Nonparametric regression analysis has become central to economic theory. Hardle, by writing the first comprehensive and accessible book on the subject, contributed enormously to making nonparametric regression equally central to econometric practice.
(30293 views)
Bayesian Field Theoryby J. C. Lemm - arXiv.org
A particular Bayesian field theory is defined by combining a likelihood model, providing a probabilistic description of the measurement process, and a prior model, providing the information necessary to generalize from training to non-training data.
(9972 views)