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3 cards from this section. Quick, good the night before a test.
What does λ represent in quality control using the Poisson distribution?
Think about what average means in the context of defect occurrence.
In a manufacturing process, if a company finds 2 defects in 100 products, what is the approximate defect rate?
Calculate the defect rate based on the ratio.
What does λ stand for in Poisson distribution for quality control?
Recall what λ defines in the context of defects.
True or False: The Poisson distribution can only model defects in manufacturing.
Consider other fields where counts of events can be random.
A factory claims that, on average, 1 in every 20 products is defective (λ=0.05). If they produce 1000 units, what’s the probability that less than 10 units are defective?
Calculate for each k using cumulative probability.
If a company observes on average 10 defects per 500 items, how does this defect rate influence their production strategies?
Consider how defect rates can inform resource allocation and process improvements.
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