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What is Coefficient of Multiple Determination?

In simple terms, it measures the proportion of variance in an independent is generally computed using two ideologies –

  1. Errors of prediction
  2. variance of prediction values in reference to the variance of observed values

The equation used for simple regression can easily be extended to the case of multiple regressive analyses. The fundamental relationship of the variance of the dependent variable predicted values and the variance of errors of prediction remain the same.

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What does the different values and variant means?

Now, it is important to know what these values actually denotes –

  • Dependent variables – these are the variable whose values one can easily predict.
  • Independent Variables – One variable that predicts the value of dependent variable.
  • Filters – optionally entering data to include a particular subgroup

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