-----Original Message-----
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED]]On
Behalf Of Jay Warner
Sent: Friday, April 05, 2002 4:29 PM
To: [EMAIL PROTECTED]
Cc: [EMAIL PROTECTED]
Subject: Re: Auxiliary regression
Amen to that.
the 'problems' that Excel has with statistics seems to appear with
various types of regression on less-than-well-cornformed data. any
regression analysis deserves as many tests of 'legitimacy,' robustness
etc. as you can give it. SPSS is one way to get a heck of a lot more
such tests than Excel.
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Not entirely true. A lot of the comments against EXCEL are like folk-tales,
like the folk tale about someone putting a JATO unit on a car (The Darwin
Awards....) someone heard it, passed it on, etc...
I have been doing a paper on the problems with Excel. It is very hard to get
specifics with data so that I can verify the problem. Even McCullough made
some incorrect statements.
I can get Excel to do an accurate solution to FILLIP with an LRE of 10.2 on
the coefficients, 14.5 on the F statistics and 14.3 on the standard error.
Both McCullough and Altman report that the software they tested did not
solve FILLIP.
The MINVERSE function does a pretty good solution with near singular
matrices. I got it to work with data having X correlations of 0.999999.
Like any tool, you have to learn how to use it first. Excel is complicated
and Microsoft does not make any effort to facilitate learning it. The
commercial manuals really gloss over the stat area, because the authors do
not have stat backgrounds. The commercial books/manuals "Statistics using
Excel" etc. are grossly simplified and aimed as a primer to anybody who
wants to learn how to use the Stat add-on package.
Excel does have problems, but there are workarounds and fixes.
DAHeiser
.
.
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