Huang’s television-repair service receives an average offour TV sets per 8-hour day to be repaired. The servicemanager would like to be able to tell customers that theycan expect their TV back in 3 days. What average repair time per set will the repair shop have to achieve to pro-vide 3-day service on the average? (Assume that the arrival rate is Poisson distributed and repair times areexponentially distributed.)
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
Huang’s television-repair service receives an average of
four TV sets per 8-hour day to be repaired. The service
manager would like to be able to tell customers that they
can expect their TV back in 3 days. What average repair
time per set will the repair shop have to achieve to pro-
vide 3-day service on the average? (Assume that the
arrival rate is Poisson distributed and repair times are
exponentially distributed.)
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