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 Variables Coefficient Std Error T P Constant 20.28338.70520 2.33 0.0223 DadsHt 0.674990.12495 5.40 0.0002 R'0.2673 Adjusted R 0.2581Standard Deviation What conclusion would you make at o .05 when conducting a test to determine if there is a positive linear relationship between the variables? Mean Square Error (MSE) 23.9235 49000 There is sufficient evidence to indicate that dad's height is a negative linear predictor of height There is insufficient evidence to indicate that dad's height is a positive linear predictor of height There is sufficient evidence to indicate that dad's height is not a positive linear predictor of height There is sufficient evidence to indicate that dad's height is a positive linear predictor of height 5 6 7 8

Explanation / Answer

p - Value corresponding to the correlation is 0.0002 which is less than 0.05 so we reject Ho and conclude that there is a significant positive correlation.

Option D is correct.

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