One of the biggest factors in determining the value of a home is the square footage. The following data represent the square footage and selling price (in thousands of dollars) for a random sample of homes for sale in Naples, Florida in January 2015.
Square Footage, x Selling Price ($000s), y
2204.....................................................379.9
3183........................................................375
1128.....................................................189.9
1975........................................................338
3101.....................................................619.9
2769........................................................370
4113......................................................627.7
2198........................................................375
2609........................................................425
1708.....................................................298.1
1786........................................................271
3813.....................................................690.1
(a) Which variable is the explanatory variable?
(b) Draw a scatter diagram of the data.
(c) Determine the linear correlation coefficient between square footage and asking price.
(d) Is there a linear relation between the square footage and asking price?
(e) Find the least-squares regression line treating square footage as the explanatory variable.
(f) Interpret the slope.
(g) Is it reasonable to interpret the y-intercept? Why?
(h) One home that is 1465 square feet is sold for $285,000. Is this home's price above or below average for a home of this size? What might be some reasons for this price?