Hi,
I'm looking for books or references on "Statistical process control".
Does anyone could give me such references.
thank you,
--
Franck GOLLIOT
===
This list is open to everyone. Occasionally, less thoughtful
people
Hi All
I look for a refrence on statistical analysis ( discrete probabality
distribution and survival function) for dispersal random distance,
(animal movement).
thank you.
===
This list is open to everyone. Occasionally,
Im a statistics student in sweden who needs some help.
Im running a best subsets (regression) and I get the following
output:
Response is skad_tot
D n a
k r y n
o
I just downloaded LEM also and the manual, which as you said is in
POSTSCRIPT format, is readable by what I assume are various sources, but the
one I have is GHOSTSCRIPT; do a search for GHOSTSCRIPT and you can download
it for free...in the old days it was kind of a pain to read PS files as
yo
On Tue, 30 May 2000, Niklas Hansen wrote:
> I'm a statistics student in sweden who needs some help.
> I'm running a best subsets (regression) and I get the following
> output:
< output deleted >
> What I would like to know is what does the statistic C-p mean?
> I would be very
Hello all,
when discussing linear regression assumptions with a colleague, we
noticed that we were unable to explain WHY heteroscedasticity has
the well known ill effects on the estimators' properties. I know
WHAT the consequences are (loss of efficiency, tendency to
underestimate the standard er
This may not fully answer all your questions, but the various formulas
for inference for regression have a place where you plug in THE
variance of the points around the regression model, i.e., they treat
this as a constant. If it is not a constant, the results of the
formulas will not be correct
Can someone emlighten me about how partial least squares regression works to
handle multicollinearity. Can SPSS do partial least squares regression?
Karen Scheltema, M.A., M.S.
Statistician
HealthEast
1700 University Ave W
St. Paul, MN 55104
(651) 232-5212 fax: (651) 641-0683
___
What is the usual cutoff for saying the VIF is too high?
Karen Scheltema, M.A., M.S.
Statistician
HealthEast
1700 University Ave W
St. Paul, MN 55104
(651) 232-5212 fax: (651) 641-0683
Get Your Private, Free E-mail from M
If you do some searching at http://www.palmgear.com you should be able to
find some function sets that work with the RPN calculator. There is also a
nice statistical analysis package called Palm Stat. PalmGear also has that -
search for "palm stat".
Eric Turkheimer wrote:
> Is there a good stati
Does not appear to be moving that direction with Minitab itself. They are
teaming with Hertzler Systems (www.hertzlersystems.com) and Qualifine to
jointly provide what looks to be a very nice real-time SPC system. Contact
qualifine (www.qualifine.com I think) to find out more. I'm sure Minitab cou
Karen..off the top of my head, the VIF is the inverse of tolerance, hence,
if tolerance = (1 - r^2j), then VIF=
1/(1-r^2j)..[excuse the sloppiness of the notation, but r^2j would be the
percentage of variation accounted for by the predictors in predicting the
other predictor..ie., the linear combi
It is 10. I hope, you are talking about Variance Inflation Factor. More than
10 indicates severe multicollinearity.
Jin
Jineshwar Singh, Coordinator, IDS
Interdisciplinary Department
George Brown College
St .James campus
[EMAIL PROTECTED]
*
You cannot control how other
On Tue, 30 May 2000, Karen Scheltema wrote:
> Can someone enlighten me about how partial least squares regression
> works to handle multicollinearity.
Depends partly on whether you're looking at real, or spurious,
multicollinearity; and may depend on where the multicollinearity
actually ari
On Tue, 30 May 2000, Dale Glaser wrote:
> Karen..off the top of my head, the VIF is the inverse of tolerance,
> hence, if tolerance = (1 - r^2j), then VIF = 1/(1-r^2j)..
Yes, Dale is correct.
> ... r^2j would be the percentage of variation accounted for by the
> predictors in predicting the o
Karen Scheltema wrote in message <[EMAIL PROTECTED]>...
>What is the usual cutoff for saying the VIF is too high?
I don't see that there can be any general criterion for saying that
a VIF is too large. A large value indicates collinearity between
predictor variables. In some fields, this cann
In article <000701bfca86$f831b9a0$047c6395@sprint>, [EMAIL PROTECTED]
says...
>
>It is 10. I hope, you are talking about Variance Inflation Factor. More
than
>10 indicates severe multicollinearity.
And where does this magic number come from? :)
>Jin
>
>Jineshwar Singh, Coordinator, IDS
>Inte
>>It is 10. I hope, you are talking about Variance Inflation Factor. More
>than
>>10 indicates severe multicollinearity.
>
>
>And where does this magic number come from? :)
>
>
Neter, Wasserman, Nachtsheim, and Kutner, of course! (or is it Wasserman,
Kutner, Neter, and Nachtsheim or one of the o
On 31 May 2000, Vmcw wrote:
> >>It is 10. I hope, you are talking about Variance Inflation Factor.
> >>More than 10 indicates severe multicollinearity.
Thus spake Jin Singh. And someone else (was it Dave Heiser?) retorted,
sensibly I thought,
> >And where does this magic number come from? :)
Please help me to solve this problem, I am stuck...
An inspector inspects large truckloads of potatoes to determine the
proportion p in the shipment with major defects prior to using the potatoes
to make potato chips. Unless there is clear evidence that this proportion
is less than 0.10 she will
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