**Basic Data Analysis and More: A Guided Tour Using Python**

by O. Melchert

**Publisher**: arXiv 2012**Number of pages**: 62

**Description**:

In these lecture notes, a selection of frequently required statistical tools will be introduced and illustrated. They allow to post-process data that stem from, e.g., large-scale numerical simulations. From a point of view of data analysis, the concepts and techniques introduced here are of general interest and are, at best, employed by computational aid. Consequently, an exemplary implementation of the presented techniques using the Python programming language is provided.

Download or read it online for free here:

**Download link**

(910KB, PDF)

## Similar books

**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.

(

**16287**views)

**Seeing Theory: A visual introduction to probability and statistics**

by

**T. Devlin, J. Guo, D. Kunin, D. Xiang**-

**Brown University**

The intent of the website and these notes is to provide an intuitive supplement to an introductory level probability and statistics course. The level is also aimed at students who are returning to the subject and would like a concise refresher ...

(

**7829**views)

**Introduction Probaility and Statistics**

by

**Muhammad El-Taha**-

**University of Southern Maine**

Topics: Data Analysis; Probability; Random Variables and Discrete Distributions; Continuous Probability Distributions; Sampling Distributions; Point and Interval Estimation; Large Sample Estimation; Large-Sample Tests of Hypothesis; etc.

(

**26783**views)

**An Introduction to Stochastic PDEs**

by

**Martin Hairer**-

**arXiv**

This text is an attempt to give a reasonably self-contained presentation of the basic theory of stochastic partial differential equations, taking for granted basic measure theory, functional analysis and probability theory, but nothing else.

(

**13170**views)