**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

**Design of Comparative Experiments**

by

**R. A. Bailey**-

**Cambridge University Press**

This book develops a coherent framework for thinking about factors that affect experiments and their relationships, including the use of Hasse diagrams. The book is ideal for advanced undergraduate and beginning graduate courses.

(

**16113**views)

**Convergence of Stochastic Processes**

by

**D. Pollard**-

**Springer**

Selected parts of empirical process theory, with applications to mathematical statistics. The book describes the combinatorial ideas needed to prove maximal inequalities for empirical processes indexed by classes of sets or classes of functions.

(

**10045**views)

**Inverse Problem Theory and Methods for Model Parameter Estimation**

by

**Albert Tarantola**-

**SIAM**

The first part deals with discrete inverse problems with a finite number of parameters, while the second part deals with general inverse problems. The book for scientists and applied mathematicians facing the interpretation of experimental data.

(

**11071**views)

**Lectures on Stochastic Analysis**

by

**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.

(

**9219**views)