I see your point Robert, and I hope you didn't think I was curt in my
response (which I may have been). Your message was quite informative. I
did meet an on-site statistician who has pledged to help me. I'm
particularly interested in the square root transformation. I'm guessing it
will compres
I have a question in regards to which test statistic to use. Example:
my problem is a test of glue "A" vs glue "B". I have a test that just
determines if glue "A" remains stuck to the surface or not. The test
does not have any other measurements. It holds or does not hold. If I
test 5 sample
On Mon, 10 Jan 2000 18:33:47 -0800, "Dave and Kim Nulton"
<[EMAIL PROTECTED]> wrote:
> Quite frankly Robert the details are proprietary. I suppose I could have
> been more descriptive, but I don't see what the shape of my distribution
> have to do with what it represents. I have received severa
dennis roberts wrote:
>
> happy new year to everyone ... hope your y2k +1 year is great!
>
> now, the y2k scare provides us with an excellent example of confounds (more
> or less) .. consider the following:
>
> Time One: lots of hype about "potential" disasters related to y2k ... (PRETEST)
Dave Nulton wrote:
> Quite frankly Robert the details are proprietary. I suppose I could have
> been more descriptive, but I don't see what the shape of my distribution
> have to do with what it represents
Well, our expertise is also proprietary!-)
_
| | Robert W. Hayden
Statistical Software Analyst/Programmer III
Bloomington, Indiana, USA
Under minimal supervision, responsible for technical support and
consultation with users for statistical software. Support statistical
software across all University Information Technology Services (UITS)
supported platforms (w
Dave Nulton wrote:
> Quite frankly Robert the details are proprietary. I suppose I could have
> been more descriptive, but I don't see what the shape of my distribution
> have to do with what it represents
To take the second point first, the origin of a dataset often contains
valuable infor
GLMStat is a Macintosh-based (NOTE: currently no Windows or UNIX
version) statistical program for analysing generalised linear
models. Features of GLMStat are
- spreadsheet style data entry
- factors may be represented as either integers or strings (categories)
- Normal, Poisson, Binomial and
