Thank for your reply! "Rich Ulrich" <[EMAIL PROTECTED]> wrote in message news:[EMAIL PROTECTED] > On Mon, 01 Dec 2003 02:33:13 GMT, "jackson marshmallow" > <[EMAIL PROTECTED]> wrote: > > > Hello everyone, > > > > I hope I can get simple answers to these questions... I need to solve a > > couple of practical problems and I'm new to statistics... > > > > 1) Two samples of are given and I need to compare their means and variances. > > I did not notice this at first reading -- you say that you > want to compare the variances, too. >
I'm not sure yet, but I may need to look into that... > Variance differences make it difficult to do tests of means, > and more, it can make it difficult to interpret them. The > group with REALLY big variance will have the extreme > scores in both directions: Otherwise, you are talking > about something that I would consider to be confounded > with *scaling* questions. Are you absolutely sure that > you are interested in the difference of the 'arithmetic > mean'? and not the 'central tendency', or the superiority > at one end or the other? > The thing is, there's more than one problem here... In one case, I may need to compare means, in another variances... > > So, look at your plots. Similar? Shifted? Expanded? > You could do several varieties of tests and see if they > all come out the same, as a cheap version of 'testing for > normality.' That's the easiest step, when you don't want > to commit to anything about the numbers. > Ultimately the basic statistical calculations will have to be automated for large amount of experiments, and I will not be able to build / examine plots for most of them. Of course, it won't hurt to do a sanity check every now and again... > Oh, the basic, simple, usual nonparametric tests that use > ranks have assumptions that are almost as harsh as those > of the t-test, so you can't really opt out of all thinking merely > by employing that rank transform. > Yes, so I understand. That would be too easy :) > > > The distribution of the population is unknown. Can I use the F-test and the > > t-test? Is it necessary that the sample _means_ have a Gaussian > > distribution? Is it sufficient? Maybe I misunderstand something here... > > If there are no outliers, then the t-test is pretty robust > for the means. A test on ranks is not exactly a test on means. > > > 2) I need to calculate the significance of correlation between two > > sequences. I would actually prefer to use randomization, but the sequences > > may be too short. Another option is to perform linear regression and > > calculate the significance of the slope using a t-test (?). When is it > > valid? > > As Dave says -- if you have a sequence where the word > 'sequence' is meaningful, then you have to take that into "sequences of numbers" is all I meant; maybe I'm misusing the term > account; simple zero-order correlation (or regression) gives > bogus values and tests when there is dependency. > > > -- > Rich Ulrich, [EMAIL PROTECTED] > http://www.pitt.edu/~wpilib/index.html > "Taxes are the price we pay for civilization." . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
