The CEO of a regional telephone company picked up the April19 Washington Post and began reading on page D1:

The Federal Government completed the biggest auction in history today, selling off part of the nation's airwaves for $7 billion to a handful of giant companies that plan to blanket the nation with new wireless communications networks for telephones and computers...

The CEO read the article with interest because his firm is scrambling to secure loans to purchase one of the licenses the FCC plans to auction off in his region next year. The region serviced by the firm has a population that is 7 percent greater than the average where licenses have been sold before, yet the FCC plans to auction the same number of licenses. This troubled the CEO, since in the most recent auction 99 bidders coughed up a total of $7 billion--an average of $70.7 million for a single license.

Fortunately for the CEO, the Washington Post article contained a table summarizing the price paid per license in 10 different regions, as well as the number of licenses sold and the population of each region. The CEO quickly entered this data into his spreadsheet, clicked the regression tool button, and found the following relation between the price of a license, the quality of licenses available, and regional population size (price and population figures are expressed in millions of dollars and people, respectively):

ln P= 2.23 - 1.2 ln Q + 1.25 ln Pop

Question1: How much money does he expect his company will need to buy a license?

Question 2: How much confidence do you place in this estimate? Can you make this calculation with the information provided?