Estimating the Mean for a Batch of 50 Items Using the Poisson Distribution

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SUMMARY

The discussion focuses on estimating the mean number of defective items in a batch of 50 using the Poisson distribution, given that a machine produces an average of 4 defective items per 100. The calculated mean for the batch of 50 is confirmed to be 2. The Poisson probability formula is applied, with the random variable X representing the number of defective items. An estimation technique yields a lambda value of approximately 4.8, which is crucial for calculating the probability of finding 3 defective items in the batch.

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  • Basic knowledge of estimation techniques for statistical parameters
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Statisticians, quality control analysts, and anyone involved in manufacturing processes who needs to estimate defect rates using the Poisson distribution.

naspek
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A machine on average produces 4 defective items out of a batch of 100 items.
Find the probability that a batch of 50 items has 3 defective items in it using the Poisson probability distribution.

the problem is..
i just want to know the mean or average value for batch of 50 items..
i got mean = 2
because for 100 items, the mean is 4..
...for 50 items, the mean would be 2..
correct?
 
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Here's how I would start it. Let the random variable X be the number of defective items in a batch of 50. P(X = 1) = 0.04.

Assuming that X is Poisson with mean lambda,
P(X = k)~= ~\frac{\lambda^k~e^{-k}}{k!}
We also have P(X = 1) = 0.04, so using the equation above, I get
\frac{\lambda^1~e^{-\lambda}}{1}~=~0.04

This isn't an equation that you can solve analytically, but you can use estimation techniques to get approximate values for lambda. In about a minute I got a value for lambda of about 4.8. The better you estimate for lambda is, the better your calculation for P(X = 3) will be.
 

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