On Mon, 2 Dec 2002 11:04:24 +0100, "Daniel Hoppe" <[EMAIL PROTECTED]> wrote:
> I've a question regarding a goodness-of-fit to a Poisson distribution. I > have the following observations from a buying process which I expect to be > Poisson.distributed: > > 0 1 2 > 182 15 3 > > The mean and my estimator for lambda in the poisson distribution therefore > is 0.105 with the following expected frequencies: > 0 1 >1 > 180.0649 18.90681 1.028281 > > Now I would like to run a chi-squared goodness-of-fit test. But for this > test the expected frequencies should be >= 5, so I would need to join > classes "1" and ">1". If I have two classes and one estimated parameter, the One fuller statement of the 'rule' says that you want no more than 25% of the Expectations less than 5, and none less than 0. What is relevant here is that we are talking about rules-of-thumb. The penalty for violating a rule of thumb is that your test is not distributed as ideally as you would like, so that (for instance) it might tell you p = .01 when it should be p= .04 . The function and reason for this particular rule of thumb is to keep you from dividing a big deviation by a tiny denominator and getting a huge chisquared contribution for that cell. For your data, you don't have a X2 that suggests non-fit. > degrees of freedom should be 2 - 1 - 1 = 0 for the test which leads me to > the assumption that this is not a good idea and that I'm missing something. ... Does this computed test have 1 d.f. then? Seems right.... -- Rich Ulrich, [EMAIL PROTECTED] http://www.pitt.edu/~wpilib/index.html . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
