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As predictors become more highly correlated, I. the p-values of the beta estimates become smaller II. it becomes more difficult to determine which predictor is actually producing the effect on the response III. the values of the beta estimates all approach zero

Respuesta :

Answer:

Hence P values of beta becomes smaller(< 0.0001). and doest affect the mean response

Step-by-step explanation:

Given:

AS Predictor  become more highly correlated .

To find:

Descriptive  Nature of high correlated Predictor .

Solution:

A predictor is high correlated means:

1)It means that the two variables are strongly related to each other.

2)This is also called as problem of multicollinearity when two variables are

in Regression.

Effects when predictor are highly correlated ;

  1. The estimated coefficient of one any one variable depends on the other predictor variable in model.
  2. Estimated coefficient of regression decrease as predictor variables are added.
  3. Hypothesis test Beta = zero gives different conclusion depending   upon variable.
  4. High correlated of predictor variable does not provide good precision of predication of response in within model.

In short ,Mulitcollinearity does not affect the mean response and  new response of the model.

Hence P values of beta becomes smaller(< 0.0001). and doest affect the mean response

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