An accountant, Keepallyer Munny, had been losing business to a competitor down the street because of TV ads put out that said the lines were too long and the turnaround time was to slow at during tax time at Munnys. K. Munny thought this was untrue and had data from the previous year but had forgotten to record how many cases there were on average from March 1 April 15 and also forgot to keep track of how long on average each one took to get processed and returned to the customer. From the data in K. Munnys computer system it was possible to calculate the average arrivals, an average rate of 20 requests for tax prep per day and the average number of taxes completed in a day, an average rate of 30 tax preps. Further, the arrivals and completions were not exponential, but instead had a variance of 4 hours^2 for arrivals of requests for tax prep and a variance of 2 hours^2 for the rate of completing tax preps. K. Munnys competitor claims turnaround times of half a day. Assume K. Munny is a crazy workaholic and works 24 hours a day.

1. How many tax preps are waiting to be completed on average? How many are at K. Munnys office on average? [In queue, in system]

A. [3.2, 5.3]

B. [2.2, 4.9]

C. [2.8, 4.1]

D. [3.9, 4.6]

2. How long (in hour) does it take for K. Munny to start working on a tax prep on average? How long (in hour) does it take to get the tax prep back to the customer in total on average? (hint: average waiting) [In queue, in system]

A. [3.3, 4.1]

B. [4.7, 5.5]

C. [4.3, 5.1]

D. [3.0, 7.2]