During registration at Tech every quarter, students in theDepartment of Management must have their coursesapproved by the departmental advisor. It takes the advisoran average of five minutes (exponentially distributed) toapprove each schedule, and students arrive at the adviser’s office at the rate of 10 per hour (Poisson distributed). Com-pute L, Lq, W, Wq, and . What do you think about this system? How would you change it?
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!
During registration at Tech every quarter, students in the
Department of Management must have their courses
approved by the departmental advisor. It takes the advisor
an average of five minutes (exponentially distributed) to
approve each schedule, and students arrive at the adviser’s
office at the rate of 10 per hour (Poisson distributed). Com-
pute L, Lq, W, Wq, and . What do you think about this
system? How would you change it?
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