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Jun 1, 2010 3:21 AM
(329 views)

I'm not even sure this is the right place to ask, but here goes.

Right now I'm working with multiple regressions in JMP. I have Y as the abundance of bees in a certain area, and several X variables such a temperature, land use area, amount of flowers and so forth.

Right now I know the values of Y and X, and I'm trying to narrow the X variables down, so only 3-5 will remain as the significant variables determining bee-abundance.

Will I be able to, via JMP, to create a model where I'll be able to input new values and then get the corresponding Y (number of bees)? Say that I would like to examine the effect of a rise in temperature. I would like to be able to punch in the new temperature, and then get the new Y value. Sort of a prediction tool for bee abundance.

Hope this was clear enough.

Best Regards, Boll

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Jun 1, 2010 5:33 AM
(297 views)

A new column with the prediction formula for your model is created and if you add new rows and enter x values the corresponding Y-values is automatically calculated (however the model is not automatically re-fitted to the new data).

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Jun 1, 2010 6:26 AM
(297 views)

Then only problem with this method: The predicted column doesn't match the actual Y values that I have. Perhaps this this question reflects my JMP knowlegde, but shouldn't they be the same? I mean if I use my Y and X values to create a formular that can predict new Y values from new X values, shouldn't the formular be able to predict the old Y values from the old X values?

Thank you very much for the help,

Dennis

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Jun 1, 2010 6:53 AM
(297 views)

In summary, the prediction formula should be able to predict your Y's reasonably well, but don't expect them to do any exact fits. However if the prediction is way off for the majority of the old Y's then the model is not good.

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Jun 3, 2010 4:43 AM
(297 views)

Nice with the profiler tool. :) I always find a useful to visualize my result. I will definitely be working some more with that.

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Jun 1, 2010 8:05 AM
(297 views)

The answer to this is yes. In the Fit Model platform, from the main hot spot (red triangle) for the model, you can select Factor Profiling > Profiler.

This will give you interactive graphs showing the effect of each X on Y.

There is a vertical dotted red line on each graph ... you can drag this to change the X value for the prediction that shows on the Y axis. The current X value is shown as a red number just below the x-axis ... you can over-type this number to enter directly the value of X for which you want to make the prediction.

The prediction is based on the model, and is only as good as the model, which in turn is dependent on the X's you have in the model (i.e. do you have data that can act as predictors) and the structure of the model (e.g. interactions between predictors).