Analysis: Scientific
[Part 8 of 12]


In this part we'll look at maths, stats, and other analysis tools. We'll cover the key texts for mathematical programming, look at R as a language and as a library for interacting with from Java, we'll look at graph theory and network analysis tools, and then look at natural language processing.


First up, maths and statistics, including a brief introduction to R.


Screenshot: A slide from the powerpoint

Maths and Stats (powerpoint)

Further info:

 

Maths libraries:
Colt
JScience
JAMA

R:
R
Comprehensive R Archive Network (CRAN)
Introduction to R
James Cheshire’s blog
R-Forge
Java interaction libraries

David Goldberg (1991) What Every Computer Scientist Should Know About Floating-Point Arithmetic ACM Computing Surveys, 23/1, 5–48


Next up, graph theory and network analysis


Further info:

Pajek
Inflow
Social network analysis software on Wikipedia
GUESS
JUNG library

Screenshot: A slide from the powerpoint

Graph theory and networks (powerpoint)


Finally, a look at natural language and text analysis.


Screenshot: A slide from the powerpoint

Language and text (powerpoint)

Further info:

 

RegEx Tutorial
Natural Language Toolkit (Python)
OpenNLP (Java) and examples


[Key ideas walked through in associated practical]