Q 100,000 110,000 125,000 150,000 215,000 300,000 400,000 450,000 475,000

P 1,500 1,400 1,300 1,200 1,100 1,000 900 800 700

3. The data in the table above represents quantity demanded (Q) and price (P) for iPhones. Use this data to answer the following questions:

(a) Enter the data for price and quantity demanded into Excel and generate a plot of P against Q (Q is on the horizontal axis and P is on the vertical axis)

(b) Use Excel to run an OLS regression of the inverse demand function: P = a + bQ + e Report your estimates for a and b. Does quantity demanded have a statistically significant effect on price?

(c) Re-run the previous OLS regression using quantity demanded in 1000's of units instead (use Q = Q/1000). How does this transformation effect your estimates?

(d) Run an OLS regression which includes both Q and Q2 as explanatory variables. What is the intuition for including the square term? Is the square term statistically significant?