Thanks Mike...I have a data with around 6 variables and I used one of them as
standard to find the relation with 5 others. now all the 5 variables had the
coc in the range of 0.6 to 0.75.

And there is high fluctuation in any one variable. Like, a single variable's
relationship with the Standard Variable varies from 0.2 - 0.8 if relationship
is calculated at different intervals of time (e.g. each day)

what do you think should be the best way to reach at some pretty reasonable
conclusion?

"Mike Middleton" wrote:

Malik -

"It all depends." But here are some comments.

First, Look At The Data. Create an XY (Scatter) chart. The correlation
coefficient measures the extent of linear relationship. It's not appropriate
for nonlinear relationships.

Second, if you're a classical statistician, take the sample size into
account. If you have a random sample and if you're really a frequentist, you
can even perform a hypothesis test to investigate whether the observed
correlation coefficient is significantly different from zero (or from some
other value).

Third, the value that is "taken seriously" varies from one discipline to
another. In psychology, you might be satisfied with r = 0.3. In economics,
you might want to see r = 0.9 or higher.

- Mike Middleton
http://www.DecisionToolworks.com
Decision Analysis Add-ins for Excel



"Malik" wrote in message
...
Do u think co-eff of co-relation is reliable? I mean two variables would
always show some relation between them no matter what. Also, at what value
of
COC should a variable be taken seriously?

Malik -

A "pretty reasonable conclusion" should depend on the context of your
problem. You don't seem to have an Excel question. Instead, you may benefit
from assistance by a statistician, data analyst, or decision analyst.

- Mike


"Malik" wrote in message
...
Thanks Mike...I have a data with around 6 variables and I used one of them
as
standard to find the relation with 5 others. now all the 5 variables had
the
coc in the range of 0.6 to 0.75.

And there is high fluctuation in any one variable. Like, a single
variable's
relationship with the Standard Variable varies from 0.2 - 0.8 if
relationship
is calculated at different intervals of time (e.g. each day)

what do you think should be the best way to reach at some pretty
reasonable
conclusion?

"Mike Middleton" wrote:

Malik -

"It all depends." But here are some comments.

First, Look At The Data. Create an XY (Scatter) chart. The correlation
coefficient measures the extent of linear relationship. It's not
appropriate
for nonlinear relationships.

Second, if you're a classical statistician, take the sample size into
account. If you have a random sample and if you're really a frequentist,
you
can even perform a hypothesis test to investigate whether the observed
correlation coefficient is significantly different from zero (or from
some
other value).

Third, the value that is "taken seriously" varies from one discipline to
another. In psychology, you might be satisfied with r = 0.3. In
economics,
you might want to see r = 0.9 or higher.

- Mike Middleton
http://www.DecisionToolworks.com
Decision Analysis Add-ins for Excel



"Malik" wrote in message
...
Do u think co-eff of co-relation is reliable? I mean two variables
would
always show some relation between them no matter what. Also, at what
value
of
COC should a variable be taken seriously?