15. In the Walton Bookstore example with a discretedemand distribution, explain why an order quantityother than one of the possible demands cannot maximize the expected profit. (Hint: Consider an orderof 190 calendars, for example. If this maximizesexpected profit, then it must yield a higher expectedprofit than an order of 150 or 100. But then an orderof 200 calendars must also yield a larger expectedprofit than 190 calendars. Why?)
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!
15. In the Walton Bookstore example with a discrete
demand distribution, explain why an order quantity
other than one of the possible demands cannot maximize the expected profit. (Hint: Consider an order
of 190 calendars, for example. If this maximizes
expected profit, then it must yield a higher expected
profit than an order of 150 or 100. But then an order
of 200 calendars must also yield a larger expected
profit than 190 calendars. Why?)
Step by step
Solved in 2 steps