Re: Bell curves -- MIDRANGE-L

× The internal search function is temporarily non-functional. The current search engine is no longer viable and we are researching alternatives.
As a stop gap measure, we are using Google's custom search engine service.
If you know of an easy to use, open source, search engine ... please contact support@midrange.com.

On 12/21/2015 6:30 PM, Booth Martin wrote:

I have a large data pile to review regularly and find exceptions. Its
looking at first blush that I am looking at lots and lots of bell curves
with a desire to isolate and review only the items that have irregular
bell shapes.

This seems to me like a problem that must occur regularly in the DB2
world? There must already be paradigms for doing this? Any
experiences, pointers, or suggestions on ways to approach this?

This is an entire field of scholarly research.

I use the programming language R for this sort of analysis. My boss is
visual, and she sees patterns in graphs and charts that I can't.
https://www.r-project.org/

Reaching in to DB2 uses JDBC.

drv <- JDBC("com.ibm.as400.access.AS400JDBCDriver",
"c:/buck/jt400/lib/jt400.jar", identifier.quote='"')
conn <- dbConnect(drv, "jdbc:as400:my.ibmi.com")
a <- dbReadTable(conn, "MYLIB.MYTABLE")
-or-
a <- dbGetQuery(conn, "select rlat, rlon, income from MYLIB.MYTABLE
where substr(rzip, 1, 3) = '021'")

This mailing list archive is Copyright 1997-2024 by midrange.com and David Gibbs as a compilation work. Use of the archive is restricted to research of a business or technical nature. Any other uses are prohibited. Full details are available on our policy page. If you have questions about this, please contact [javascript protected email address].

Operating expenses for this site are earned using the Amazon Associate program and Google Adsense.