The sampling distribution, the distribution of x-bars, for n = 49 (a large sample, n > 30) is approximately normal with mean = 250 and standard deviation = 50/7 = 7.14. The z-score for 260 is (260 -
2 50)/7.14 = 1.40. The table value for 1.4, P(x-bar 260), is 0.9192. P(x-bar > 260) = 1 - 0.9192 = 0.0808.
So, the probability the 49-member accounting department has an average expenses of more than $260 is
8 .1% (to nearest 0.1%).

EPS(0) = $1.00. DOL = 1.25. EPS(1) = ? %Change S = 15%. DFL = 3.50. DTL = DOL(DFL)
= 1.25(3.50) = 4.375. EPS(1) = EPS(0)[1.0 + (DTL)(%Change Sales)] = $1.00[1.0 + (4.375)(0.15)] =
$ 1.00[1.6563] = $1.6563.

All of the other answers reduce receivables days. A key assumption of the receivables days calculation is that sales occur at a fairly constant level. If however, there is any form of sales build-up towards the end of the financial year, then the receivables days can be misleading. A large sale near the end of the year would increase sales and also the ending balance in Accounts Receivable.

Relative to perfectly competitive industries, monopolies will restrict output, allowing them to charge a higher price and make a profit. This results in a net loss of benefits to society.

Since the monopolistic competitor operates where P = ATC in the long run and MC ATC for the firm then it is true that P > MC