2. Suppose that you have been asked to estimate a regression model to explain the number of people jogging a mile or more on the school track to help decide whether to build a second track to handle all the joggers. You collect data by living in a press box for the spring semester, and you run two possible explanatory equations:

A: Y = 125.0 - 15.0X1 - 1.0X2 + 1.5X3 R2 = .75

B: Y = 123.0 - 14.0X1 + 5.5X2 - 3.7X4 R2 = .73

where: Y = the number of joggers on a given day

X1 = inches of rain that day

X2 = hours of sunshine that day

X3 = the high temperature for that day (in degrees F)

X4 = the number of classes with term papers due the next day

1. Which of the two (admittedly hypothetical) equations do you prefer? Why?
2. How is it possible to get different estimated signs for the coefficient of the same variable using the same data?