A commemorative coin company has two stamping machines. The faster one can stamp 150 coins per hour of which about 3 are defective. The slower machine can stamp 70 coins hour of which about 14 are defective. All coins are deposited into a common hopper. After the first hour of the day (assuming the hopper was initially empty), a coin is removed from the hopper and tested to be defective. What is the probability it was stamped by the slower machine? State your answer as a decimal rounded to 4 decimal places.
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!
A commemorative coin company has two stamping machines. The faster one can stamp 150 coins per hour of which about 3 are defective. The slower machine can stamp 70 coins hour of which about 14 are defective. All coins are deposited into a common hopper. After the first hour of the day (assuming the hopper was initially empty), a coin is removed from the hopper and tested to be defective. What is the probability it was stamped by the slower machine? State your answer as a decimal rounded to 4 decimal places.
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