home *** CD-ROM | disk | FTP | other *** search
- Newsgroups: bit.listserv.qualrs-l
- Path: sparky!uunet!utcsri!torn!nott!cunews!tgee
- From: tgee@alfred.carleton.ca (Travis Gee)
- Subject: Re: Coding in qualitative analysis
- Message-ID: <tgee.727757659@cunews>
- Sender: news@cunews.carleton.ca (News Administrator)
- Organization: Carleton University
- References: <QUALRS-L%93012213081569@UGA.CC.UGA.EDU>
- Date: Sat, 23 Jan 1993 02:54:19 GMT
- Lines: 36
-
- In <QUALRS-L%93012213081569@UGA.CC.UGA.EDU> Al Futrell <AWFUTR01@ULKYVM.BITNET> writes:
-
- >Travis: The following point you make is interesting. Are you
- > quantifying some measure to determine whether or not you
- > have committed these errors or are you using Type I and
- > Type II as metaphors for the errors that a qualitative
- > approach (researcher) might make?
- -----point not repeated--------
-
- My use of "Type I" and "Type II" just referred to the *kind* of
- errors that were being made, with no implication abut statistical
- measures. (Some were used in my study, but I used a pretty minimalist
- approach to stats, at least by today's number-crunching standards.)
- The key point is that qualitative methods can be prone to such errors,
- because we make assertions based on data. In the spirit of this group
- I am loath to require quantification of such errors and am rather more
- interested in the form of the errors we researchers can make.
- Reviewing the >snippet above, I would also like to comment on the
- word "metaphor". I think it's a bit strong. Type I and Type II
- errors *can* have probabilistic statements made about them in some
- contexts. However, it is the *nature* of the error (i.e., saying it's
- there when it's not, or vice-versa) to which we refer. Thus, in point
- of fact I would hazard a guess that the requirement of quantification
- to which I referred in the preceding paragraph is actually an artefact
- of our deference to statistics and not at all necessary.
- Hope I said this all in something resembling correct English....
-
- ((((((((((((((((((((((((((((((((((((((((((((((((((((((((((
- Travis Gee () tgee@ccs.carleton.ca ()
- () tgee@acadvm1.uottawa.ca () ()()()()
- () () ()
- () ()()()()()()()()()
- Recent government figures indicate that 43% of all statistics
- are utterly useless.
-