A process is considered to be performing to acceptable standards if its mean is at least 300. To determine whether the process has to be reconfigured, a plant manager wants to determine if there is evidence that the process mean is below 300. Experience has shown that the process is normally distributed with a standard deviation of 20. In this situation, a Type I error would be made when it is concluded that µ is 300 when in fact µ is 300. not equal to; equal to equal to; greater than below; equal or greater than greater than; less than or equal to
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 process is considered to be performing to acceptable standards if its mean is at least 300. To determine whether the process has to be reconfigured, a plant manager wants to determine if there is evidence that the process mean is below 300. Experience has shown that the process is
- In this situation, a Type I error would be made when it is concluded that µ is 300 when in fact µ is 300.
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below; equal or greater than |
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