================================================================== The gateway between this list and the sci.stat.edu newsgroup will be disabled on June 9. This list will be discontinued on June 21. Subscribe to the new list EDSTAT-L at Penn State using the web interface at http://lists.psu.edu/archives/edstat-l.html. ================================================================== . A lot depends on WHY you are trying to categorize this variable. In fact, for many pruposes, categorizing a variable is not a good idea.
If your problem is that this variable is distributed very non-nonnormally, then a log transformation may help, but without knowing what you are trying to do, and why, it is hard to recommend anything..... Peter Peter L. Flom, PhD Assistant Director, Statistics and Data Analysis Core Center for Drug Use and HIV Research National Development and Research Institutes 71 W. 23rd St www.peterflom.com New York, NY 10010 (212) 845-4485 (voice) (917) 438-0894 (fax) >>> [EMAIL PROTECTED] 6/7/2004 5:04:26 PM >>> ================================================================== The gateway between this list and the sci.stat.edu newsgroup will be disabled on June 9. This list will be discontinued on June 21. Subscribe to the new list EDSTAT-L at Penn State using the web interface at http://lists.psu.edu/archives/edstat-l.html. ================================================================== . Dear all, I should highly appreciate it if some one could advice me on how to do with this issue: I have been trying to categorise a continuous variable which is the total assets of a 295 company. The problem is that there are few clusters (of very few firms each) located a way from the highest percentiles. What I meant is that there is a huge gap between the very large ones and few others in the middle of the range the very vast majority of the sample. This made the categorisation quite cumbersome. If you were interested to know more abut the variable, the following are some of the most informative statistics. Minimum: $3.453 Million, Maximum: 207410 M, (huge range of 207407), Mean: 5019.6 M, Std. deviation: 21.367. On the other hand percentiles where: 50th: 306.4 M, 75th: 1155, 90th: 6482 and finally the 95th: 18314 Thank you, Stephen ____________________________________________________________ Yahoo! Messenger - Communicate instantly..."Ping" your friends today! Download Messenger Now http://uk.messenger.yahoo.com/download/index.html
