**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

**Lectures on Noise Sensitivity and Percolation**

by

**Christophe Garban, Jeffrey E. Steif**-

**arXiv**

The goal of this set of lectures is to combine two seemingly unrelated topics: (1) The study of Boolean functions, a field particularly active in computer science; (2) Some models in statistical physics, mostly percolation.

(

**11336**views)

**Probability and Mathematical Statistics**

by

**Prasanna Sahoo**-

**University of Louisville**

This book is an introduction to probability and mathematical statistics intended for students already having some elementary mathematical background. It is intended for a one-year junior or senior level undergraduate or beginning graduate course.

(

**11048**views)

**Applied Nonparametric Regression**

by

**Wolfgang HÃ¤rdle**-

**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.

(

**25679**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.

(

**14996**views)