**Correlation and Causality**

by David A. Kenny

**Publisher**: John Wiley & Sons Inc 1979**ISBN/ASIN**: 0471024392**ISBN-13**: 9780471024392**Number of pages**: 353

**Description**:

This text is a general introduction to the topic of structural analysis. It is an introduction because it presumes no previous acquaintance with causal analysis. It is general because it covers all the standard, as well as a few nonstandard, statistical procedures. Since the topic is structural analysis, and not statistics, very little discussion is given to the actual mechanics of estimation.

Download or read it online for free here:

**Download link**

(2.1MB, 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.

(

**12335**views)

**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.

(

**14903**views)

**Probability and Statistics for Geophysical Processes**

by

**D. Koutsoyiannis**-

**National Technical University of Athens**

Contents: The utility of probability; Basic concepts of probability; Elementary statistical concepts; Special concepts of probability theory in geophysical applications; Typical univariate statistical analysis in geophysical processes; etc.

(

**7314**views)

**Markov Chains and Mixing Times**

by

**D. A. Levin, Y. Peres, E. L. Wilmer**-

**American Mathematical Society**

An introduction to the modern approach to the theory of Markov chains. The main goal of this approach is to determine the rate of convergence of a Markov chain to the stationary distribution as a function of the size and geometry of the state space.

(

**14762**views)