Re: Analysing performance data (somewhat OT stat question; sorry)

[Henry F. Mollet]

Ny 1964 edition the Hbk of Mathematical Functions (M. Abramowity & I. A.
Stegun eds) lists the following probability functions in Chapter 26.

One dimensional discrete: Single point or degenerate, binomial,
hypergeometric, Poisson, negative binomial, geometric.

One dimensional continuous: error function, normal, Cauchy, exponential,
Laplace or double exponential, extreme value (Fishher-Tippett Type I or
doubly exponential, Pearson Type III, gamma distribution, beta distribution,
rectangular or uniform.

In addition to the name, the table gives domain, point
probability/probability density function, restriction on parameters, mean,
variance, skewness gamma1, excess gamma2, characteristic function, and
cumulants.
Henry



on 9/22/04 10:54 AM, James Knowles at address@hidden wrote:

> I've been collecting performance data for different software
> configurations, and examining it in Octave.
> 
> It's been about 15 year since college stats class, so I'm rusty. Some
> data distributions are normal, and a simple t-test works great for
> testing whether there's a significant difference between configurations.
> Many are visually "obvious," but some are not. They all need to be
> documented, however.
> 
> Some are heavily skewed, scrunched up near zero. I don't remember what
> this kind of distribution is called. I do not remember what to use here
> to test a null-hypothesis of the two data populations being the same.
> (Yes, inaccurate terminology; sorry.)
> 
> Octave has alot built in, and I don't want to just plug data in randomly.
> 
> Thanks!
> 
> 
> 
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