| Date: | Mon, 25 Apr 2005 10:10:59 +0200 |
| Reply-To: | Grado <grado2005@gamespy.com> |
| Sender: | "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU> |
| From: | Grado <grado2005@GAMESPY.COM> |
| Subject: | Re: bimodal distribution |
|
"Jim Simmons" <emailjimsimmons@YAHOO.COM> ha scritto nel messaggio
news:20050424180743.86963.qmail@web81607.mail.yahoo.com...
> Grado,
>
Or would you also like to screen for any non-normal
> distribution such as highly skewed ones, or ones with kurtosis
> problems so extreme that they are non-normal?
>
I just want to check for bimodal distribution of prices, because it may mean
there are classification problem over an item by some retailer (i.e.
retailer A codifies with EAN code xxxxx an item with average price 10, while
retailer B codiefies with the same EAN an item with average price 1000).
> Also, when you say you are checking over a thousand items do you
> mean you have to check a thousand variables(prices) in a single
> data set, in multiple data sets, or a single variable in more
> than a thousand data sets, or some combination of these
> conditions?
No, I'm checking for a thousand of distinct items with no more than 50/60
prices. So it is an extensive check without so much obs.
>What type of automated precedure is currently in use
> for this task? Macro's, SCL?
Just a simple macro. At the moment I am only highlighting extreme prices,
the ones out 5th and 95th percentile, but this approach is not adequate for
bimodal distributions.
Thank you for any suggestion.
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