Suppose that highway gas mileage rates for both of these cares are uniformly distributed over a range of from 20 to 30 mpg. What proportion of these cars would fall into the 22 to 27 mpg range? Compute the proportion of cars that get more than 28 mpg. What proportion of cars would get less than 23 mpg?
3. Suppose that in one dealership an average of 1.37 CLKs is sold every 3 hours (during a 12-hour showroom day) and that sales are Poisson distributed. The following Excel-produced probabilities indicate the occurrence of different intersales times based on this information. Study the output and interpret it for the salespeople. For example, what is the probability that less than an hour will elapse between sales? What is the probability that more than a day (12-hour day) will pass before the next sale after a car has been sold? What can the dealership managers do with such information? How can it help in staffing? How can such information be used as a tracking device for the impact of advertising? Is there a chance that these probabilities would change during the year? If so, why?
Portion of 3-Hour Time Frame Cumulative Exponential Probabilities from Left
0.167 0.2045
0.333 0.3663
0.667 0.5990
1    0.7459
2    0.9354
3    0.9836
4    0.9958
5    0.9989