Suppose you have just received a shipment of 18 modems. Although you don't know this, 4 of the modems are defective. To determine whether you will accept the shipment, you randomly select 6 modems and test them. If all 6 modems work, you accept the shipment. Otherwise, the shipment is rejected. What is the probability of accepting the shipment? round to 4 decimal places as needed
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!
Suppose you have just received a shipment of 18 modems. Although you don't know this, 4 of the modems are defective. To determine whether you will accept the shipment, you randomly select 6 modems and test them. If all 6 modems work, you accept the shipment. Otherwise, the shipment is rejected. What is the probability of accepting the shipment?
round to 4 decimal places as needed
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