Tools for analysing experimental data

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+1 Q:

Tools for analysing experimental data

What tools are there for analysing experimental data with a number of variables to attempt to optimise parameters for a particular parameter? This question is purposely general - I'm more asking for tools that I should look at in the future, than tools to use now.

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+2 A:

Have you looked at R? To quote from the FAQ:

R is a system for statistical computation and graphics. It consists of a language plus a run-time environment with graphics, a debugger, access to certain system functions, and the ability to run programs stored in script files.

Version 2.10.0 was released this week. About 2000 contributed packages are at the CRAN mirror network.

Dirk Eddelbuettel 2009-10-29 12:25:31

+1 A:

R's good, so is Matlab, Mathematica, even Excel.

Mark

High Performance Mark 2009-10-29 12:28:31

+2 A:

As far as free tools go, I second Dirk's suggestion of R, but I'd like to mention Python and the SciPy library (in particular, the scipy.optimize package) as a possible alternative. It would help of you could be more specific as to what kind of data analysis you are trying to do so that we can be more specific with our recommendations.

las3rjock 2009-10-29 12:42:56

I second your mention of Python, and would like to point out that if SciPy won't do everything that you need, you will probably find it easier to use Rpy2 to interface to R rather than having to learn the R language itself. The R language was designed by statisticians, not programmers, so a developer will get more done, more quickly with Python than with R.

Michael Dillon 2009-10-29 13:19:24

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Tools for analysing experimental data

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