3. For the slopes above, you should have gotten about .30 for the mother and .40 for the father. Why do you think a 1-inch increase in both the mother and father would only result in an associated increase of about .70 inches in height for their child? Take my family for example, my Mom is 64 inches and my Dad is 70 inches, so my predicted height according to our model was about 69.5 inches and my actual height is very close at about 70 inches. A common and simple way to predict a boys height is to add 5 inches to the Mom, then take the mean of that and the Dads height. ((64 + 5) + (70)) / 2 = 69.5. For girls, do a similar equation but with subtracting 5 inches from the Dads height ((70 5) + (64)) / 2 = 64.5 inches, and my Sister is 65 inches. The thing is though, if my parents were both 6 inches taller, this more common method would have my predicted height to be simply 6 inches taller at 75.5 inches and my Sisters at 70.5 inches. But, our multiple regression model would have me predicted to actually be shorter then my Dad at about 74 inches and my sister to similarly be shorter than my Mom at about 69 inches. What phenomenon is happening and what part of the multiple regression model that hasnt been asked about showcases it?