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Thread: Regression & Predictions

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    Exclamation Regression & Predictions




    I have a problem to work out involving forecasting/predicting:

    Given multiple data sets (variables), I need to evaluate which set is the best predictor for my dependent variable (i.e., whether or not population affects annual sales, for example).

    I ran a regression on each variable compared to the dependent variable - now which answer provides me with the "best predictor"? On one, for example, I received an r2 of 26.95%, but my t-statistic was -5.154. How can I have a t-stat which says there is no linear relationship, but an r2 that is telling me there is a high correlation (26.95% was the highest r2 received)?

    Once I determine best and worst predictors, I need to determine what the best two-factor model is; how would I go about that? With 6 different variables to evaluate, it would take forever to evaluate each two-factor possibilities.

    thanks!!

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    You should check the partial R2's for every predictor

    > http://tolstoy.newcastle.edu.au/R/help/05/03/0329.html (using R)
    > http://biol10.biol.umontreal.ca/borcardd/partialr2.pdf (Theory)

    You could do a forward or backward procedure or an Information Theoretic in general.but partial R2's would do the trick manualy in your case

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