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 Mean Square Error (MSE) 23.9235 4.9000 R' 0.2673 Adjusted R' 0.2581Standard Deviation Which interpretation of the slope estimate would be appropriate? For every additional inch in dad's height, we estimate height to increase by 675 inches. For every 675 inch increase in dad's height, we estimate height to increase by 20.28 inches. For every additional inch in dad's height, we estimate height to increase by 20.28 For every additional 20.28 inches increase in dad's height, we estimate height to increase by 675 inches. 5 7

Explanation / Answer

here as coefficient of slope is 0.675 from the output; therefore correct interpretation is :

for every additional inch in Dad;s Height we estimate height to increase by 0.675 inches

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