**Principles of Data Analysis**

by Cappella Archive

**Publisher**: Prasenjit Saha 2003**ISBN/ASIN**: 1902918118**Number of pages**: 113

**Description**:

This is a short book about the principles of data analysis. The emphasis is on why things are done rather than on exactly how to do them. If you already know something about the subject, then working through this book will probably deepen your understanding.

Download or read it online for free here:

**Download link**

(750KB, PDF)

## Similar books

**Reversible Markov Chains and Random Walks on Graphs**

by

**David Aldous, James Allen Fill**-

**University of California, Berkeley**

From the table of contents: General Markov Chains; Reversible Markov Chains; Hitting and Convergence Time, and Flow Rate, Parameters for Reversible Markov Chains; Special Graphs and Trees; Cover Times; Symmetric Graphs and Chains; etc.

(

**10638**views)

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

by

**O. Melchert**-

**arXiv**

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 (aka sequence of random experiments).

(

**10413**views)

**Probability, Statistics and Stochastic Processes**

by

**Cosma Rohilla Shalizi**

Contents: Probability (Probability Calculus, Random Variables, Discrete and Continuous Distributions); Statistics (Handling of Data, Sampling, Estimation, Hypothesis Testing); Stochastic Processes (Markov Processes, Continuous-Time Processes).

(

**8239**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.

(

**10758**views)