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| q |
Very often, one predictor is a function of the other predictors.
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| q |
It becomes an important question: How many predictors do
we
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need in order to make a good regression (or prediction)?
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| q |
Does increasing the number of the predictor improve the
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regression (or prediction)?
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| q |
If too many predictors are used, some large coefficients
may be
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assigned to variables that are not really highly
correlated to the
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predictant (y). These coefficients are generated to
help the
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regression relation to fit y.
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To answer this question, we have to figure out how fast
(or slow)
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the “fraction of explained variance” increase with additional
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number of predictors.
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