## Networks Basic Statistics

### From OPOSSEM

##### Revision as of 12:36, 7 July 2011 by Derek Ruths (talk | contribs) (Created page with "<!-- add any hidden notes here --> =Objectives= * Compute the degree distribution for undirected and directed networks * Quantify the local density of connectivity in the netwo...")

Revision as of 12:36, 7 July 2011 by Derek Ruths (talk | contribs) (Created page with "<!-- add any hidden notes here --> =Objectives= * Compute the degree distribution for undirected and directed networks * Quantify the local density of connectivity in the netwo...")

## Contents

# Objectives

- Compute the degree distribution for undirected and directed networks
- Quantify the local density of connectivity in the network
- Understand why motif distributions must be estimated in large networks

# Introduction

Fundamentally, a network is a body of data. As with other data sets, our first task it to identify significant features of that data. In much the same way as the mean and standard deviation are easy to compute but very valuable summary statistics, degree, clustering, and motif statistics are easy to compute attributes that can reveal a great deal about the structure of a network. We discuss these different basic statistics here.

# Degree Distribution

## Out and In Degrees

## Scale-free Distributions

# Clustering Coefficient

## Transitive Triples

# Motif Distributions

# Conclusion

# References

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# Discussion questions

# Problems

# Glossary

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