Whoever told you how to do this is completely wrong. For multiple regression,
you must find all parameters simultaneously. This is because X1, X2, and X3
are NOT independent.
Ken
>I am told that I can solve for these three unknowns (B1, B2 and B3) by
>doing simple linear regression to obtain "
Why would one wish to avoid multiple linear regression, which is so much
more convenient than the sequence of simple linear regressions alluded to
below? Two possible reasons occur to mind:
(1) for the challenge of finding out how to do it (in which case I
wouldn't want to spoil your fun!);
I am told that I can solve for these three unknowns (B1, B2 and B3) by
doing simple linear regression to obtain "residuals"; from the
residuals come the unknowns. For example, I know that with just two
unknowns (B1 and B2) in:
y = B0 + B1 * x1 + B2 * x2 + e
I can obtain B1 after the followin
I see this posted in three groups, and so I am posting it back to all
three.
On Thu, 10 Feb 2000 17:00:37 +0800, Alice Kwan <[EMAIL PROTECTED]>
wrote:
> I would like to know which statistical method should I use for my
> research with SPSS.
>
> My research aims at examining the causal relations
On Fri, 11 Feb 2000 15:01:25 GMT, [EMAIL PROTECTED] wrote:
> I'm working on a study that compares neural networks to classical non-
> linear statistical estimators in forecasting time series. My thesis is
> that the NN would be robust under conditions where the assumptions of
> the classical mod
As a lab guide, SPSS for Windows Step by step is very good (authors: George
and Mallery, publisher : Allyn and Bacon). There is also a very good book
for psychologists: Tabachnick and Fidell, Using multivariate statistics.
The only problem is that it does not have cluster analysis.
At 14:29
John --
Sounds very interesting--
If you mean "classical" least-squares model, there
are no assumptions involved
in fitting least-squares. It's only the
"statistics" assumptions that get added into
the extra "assumptions".
PREDICTION is the important thing.
Compare the PREDICTIVE accu
I am looking for a lab guide to teach SPSS mulitivariate stats. This book
is for psychology graduate students. Ideally, the book would have data
sets and exercises that cover multiple regression and correlation,
factorial analysis, cluster analysis, and discriminant analysis. Can
anyone recomme
Dear colleagues,
I have a large survival data set of breast cancer patients who were
treated with different therapies.
Most of the patients were treated with more than one therapy. There are
a lot of combinations of therapies in the data set.
There is the hypothesis that not only the set of appli
The question of the advisability using a control chart for this kind of
tracking may not be answerable in the affirmative. The viability of a
control chart depends on measuring a representative sample of the
population, whereas it appears that Lenin is interested in estimating the
confidence l
I'm working on a study that compares neural networks to classical non-
linear statistical estimators in forecasting time series. My thesis is
that the NN would be robust under conditions where the assumptions of
the classical model are not met, and the nn would be inferior where the
classical ass
On 10 Feb 2000, Richard M. Barton wrote:
> --- Alex Yu wrote:
>
> A statistical procedure alone cannot determine casual relationships.
> ---
>
>
> Correct. A lot depends on eye contact.
>
> rb
And also, at least 2 statistical procedures are required...
=
[EMAIL PROTECTED] wrote:
> We track a metric that consists of the fraction of hours that a machine
> was not running during a week. The numerator is the number of hours
> not running and the denominator is the number of hours running plus the
> hours not running. This is a weekly metric. I wis
Not very good at statistics, bets I did was "Introductory Econometrics"
by Ramanathan. Still got a hard question
Suppose I want to explain number of deaths of time from a fixed pool of
people (got ur attention? :)
First I assume this is a binomial process. From the data I have
collected over
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