1. Weekly demand for smartphones at an Apple store is nor- mally distributed, with a mean of 500 and a standard devia- tion of 300. Foxconn, the assembler, takes four weeks to of 95 percent, how much safety inventory of jeans should the store carry? What should its ROP be? 3. Weekly demand for Motorola cell phones at a Best Buy store is normally distributed, with a mean of 300 and a standard deviation of 200. Motorola takes two weeks to supply a Best Buy order. Best Buy is targeting a CSL of 95 percent and monitors its inventory continuously. How much safety inven- tory of cell phones should Best Buy carry? What should its ROP be? 4. Reconsider the Best Buy store in Exercise 3. The store man- ager has decided to follow a periodic review policy to man- age inventory of cell phones. She plans to order every three weeks. Given a desired CSL of 95 percent, how much safety inventory should the store carry? What should its OUL be? supply an Apple order. Apple is targeting a CSL of 95 percent and monitors its inventory continuously. How much safety inventory of cell phones should the Apple store carry? What should its ROP be? 2. Weekly demand for jeans at a Gap store is normally distrib- uted, with a mean of 100 and a standard deviation of 50. The supply plant takes three weeks to supply a Gap order. The store manager monitors its inventory continuously and reor- ders jeans when the available inventory drops below 350. How much safety stock does the store carry? What CSL does the store achieve? If the store manager wants to target a CSL
Addition Rule of Probability
It simply refers to the likelihood of an event taking place whenever the occurrence of an event is uncertain. The probability of a single event can be calculated by dividing the number of successful trials of that event by the total number of trials.
Expected Value
When a large number of trials are performed for any random variable ‘X’, the predicted result is most likely the mean of all the outcomes for the random variable and it is known as expected value also known as expectation. The expected value, also known as the expectation, is denoted by: E(X).
Probability Distributions
Understanding probability is necessary to know the probability distributions. In statistics, probability is how the uncertainty of an event is measured. This event can be anything. The most common examples include tossing a coin, rolling a die, or choosing a card. Each of these events has multiple possibilities. Every such possibility is measured with the help of probability. To be more precise, the probability is used for calculating the occurrence of events that may or may not happen. Probability does not give sure results. Unless the probability of any event is 1, the different outcomes may or may not happen in real life, regardless of how less or how more their probability is.
Basic Probability
The simple definition of probability it is a chance of the occurrence of an event. It is defined in numerical form and the probability value is between 0 to 1. The probability value 0 indicates that there is no chance of that event occurring and the probability value 1 indicates that the event will occur. Sum of the probability value must be 1. The probability value is never a negative number. If it happens, then recheck the calculation.
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