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From "Phil Steitz" <p...@steitz.com>
Subject Re: [math] proposed ordering for task list, scope of initial release
Date Tue, 10 Jun 2003 14:12:52 GMT
Brent Worden wrote:
>>-----Original Message-----

>>* t-test statistic needs to be added and we should probably add
>>the capability
>>of actually performing t- and chi-square tests at fixed
>>significance levels
>>(.1, .05, .01, .001). -- This is virtually done, just need to
>>define a nice,
>>convenient interface for doing one- and two-tailed tests.  Thanks
>>to Brent, we
>>can actually support user-supplied significance levels (next item)
> 
> 
> Anyone have any thoughts on the interface?  I was thinking of an Inference
> interface that supports the conducting of one- and two-tailed tests as well
> as constructing their complementary confidence intervals.  Or, if we want to
> separate concerns create both a HypothesisTest and a ConfidenceInterval
> interface, one for each type of inference.  Either way, I would use the
> tried-and-true abstract factory way of creating inference instances.
> Comments are welcome.

I have been thinking about this.  If I can stop sending emails for long 
enought to pull the patch together, I am about to submit a patch to 
BivariateRegression that adds the slope confidence interval computation 
and significance level, based on the new t-distribution impl (thanks, 
Brent!).  I thought about a generic ConfidenceInterval interface, but 
then thought that it would be more convenient for users to just return 
the halfwidth in double getSlopeConfidenceInterval(). To support the 
goal of testing model significance, I also added getSignificance().

I think the concrete stuff is easier to use and all we need at present. 
  Something like:

boolean twoTailedTTest(Univariate, Univariate,signif) or even
boolean twoTailedTTest(double[],double[],signif)
(obviously adding one-tailed tests and tests against constants as well 
and tests that return doubles representing minimal p-values, possibly 
called "significance")
boolean chiSquareTest(expected, observed, signif)
boolean chiSquareTest(Freq, Freq, signif)

To add the abstractions above meaningfully, we need to convince 
ourselves that either a) multiple implementation strategies might exist 
--  For parametric tests, this is not the case -- or b) the abstractions 
will make development of inferential components easier/more manageable. 
I am not sure about b). In fact, when I think about it I think that 
there is not much left when you abstract things to a high enough level 
to represent hypothesis testing and/or confidence intervals generically. 
I remember math stat students having a hard time understanding the 
abstract definitions of these concepts. I don't think that it is a good 
idea to force our users to think about these things.  Therefore, I would 
recommend sticking with concrete implementations defined "close to" the 
statistical applications.

Keep the user application use cases in mind.  If I want to determine 
whether the diffence in two means is significant, I should be able to do 
that quickly and intuitively, with one method call either using 
Univariates or double[]s.

> 
> 
>>* numerical approximation of the t- and chi-square distributions to enable
>>user-supplied significance levels.  See above.  Someone just
>>needs to put a
>>fork in this. Tim? Brent?
> 
> 
> Done.
> 



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