Is the number of square feet of living space a good predictor of a house's selling price? The following data show the square footage and selling price for fifteen houses in Winston Salem, North Carolina (Zillow.com, April 5, 2015).

Size ________________________________ Selling Price

(1000s sq. ft ) _________________________($1000s)

1.26 ................................................ 117.5

3.02 ................................................ 299.9

1.99 ................................................ 139.0

0.91 ................................................ 45.6

1.87 ................................................ 129.9

2.63 ................................................ 274.9

2.60 ................................................ 259.9

2.27 ................................................ 177.0

2.30 ................................................ 175.0

2.08 ................................................ 189.9

1.12 ................................................ 95.0

1.38 ................................................ 82.1

1.80 ................................................ 169.0

1.57 ................................................ 96.5

1.45 ................................................ 114.9

a. Develop a scatter diagram with square feet of living space as the independent variable and selling price as the dependent variable. What does the scatter diagram indicate about the relationship between the size of a house and the selling price?

b. Develop the estimated regression equation that could be used to predict the selling price given the number of square feet of living space.

c. At the .05 level, is there a significant relationship between the two variables?

d. Use the estimated regression equation to predict the selling price of a 2000 square foot house in winston Salem, North Carolina.

e. Do you believe the estimated regression equation developed in part (b) will provide a good prediction of selling price of a particular house in winston Salem, North Carolina? Explain.

f. Would you be comfortable using the estimated regression equation developed in part (b) to predict the selling price of a particular house in Seattle, washington? why or why not?