Suppose we use a person\'s dad\'s height to predict how short or tall the person
ID: 3376284 • Letter: S
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.