Suppose we use a person\'s dad\'s height to predict how short or tall the person

Question

Suppose we use a person's dad's height to predict how short or tall the person will be by building a regression model to investigate if a relationship exists between the two variables. Suppose the regression results are as follows:

Least Squares Linear Regression of Height

Predictor
Variables Coefficient Std Error T P
Constant 20.2833 8.70520 2.33 0.0223
DadsHt 0.67499 0.12495 5.40 0.0002

R² 0.2673 Mean Square Error (MSE) 23.9235
Adjusted R² 0.2581 Standard Deviation 4.9000

Which interpretation of the y-intercept estimate would be appropriate?

B) No practical interpretation is possible since dad's height=0 inches doesn't make sense.

C) For every additional inch in dad's height, we estimate height to increase by 20.28 inches.

D) No practical interpretation is possible since height=0 inches doesn't make sense.

Explanation / Answer

Sol:

Regression eq is

Height=20.2833 +0.67499 *Dads Ht

Y intercett we get When Dads Ht substituted with zero

Height=20.2833 +0.67499 *0

Height=20.2833

Does not make sense

Mark

B) No practical interpretation is possible since dad's height=0 inches doesn't make sense.

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