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Suppose you have an SLR model for predicting IQ from height. The estimated coefficient for height is positive. Now, we add a predictor for age to create an MLR model. After fitting this new model, the estimated coefficient for height must be:

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When you add a fitting this new model, the estimated coefficient for height must be Different, but still positive.

What is the SLR model about?

If there is a  positive correlation but negative regression coefficient it means that the influence or the effect of the intercorrelations that exist between the independent variables may be negative when there is a positive correlation coefficient that exist between the variable and the dependent variable.

Therefore  When you add a fitting this new model, the estimated coefficient for height must be Different, but still positive.

See full question below

Suppose you have an SLR model for predicting IQ from height. The estimated coefficient predictor for age to create an MLR model. After for height is positive. Now, we add a fitting this new model, the estimated coefficient for height must be:

  • Exactly the same as the SLR model
  • Different, but still positive
  • Zero Negative
  • None of the above

Learn more about SLR model from

https://brainly.com/question/14469391

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