a) What is the probability that the entire shipment shall be accepted? b) What is the probability that the entire shipment shall be rejected?
A shipment of 40 Mickey Mouse watches contains 6 defective ones. The shipping department selects seven of these watches and rejects the entire shipment if one or more are defective.
A shipment of 40 Mickey Mouse watches contains 6 defective ones. The shipping department selects seven of these watches and rejects the entire shipment if one or more are defective.
a) All 7 meet specification
b) At least 1 fail (rejected)
The total ways of ordering this for a sample of 7 is: Using Pascal's triangle for Binomial expansion we select Accept Defective probability given as: a) All 7 meet specification b) At least 1 fail (rejected) It is more likely the shipment will be rejected. This is very costly for the supplier. So it would be far better for them to apply 100% inspection at the manufacture point. The advantage of using the Binomial expansion is that it permits the probability calculation for any of the individual condition (or groups). Suppose I wished to determine 3 poor and 4 quality. I would use the
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Reject
Not defective is thus:
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Comment.
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To determine the probability of the entire shipment being accepted or rejected, we need to know the individual probabilities of each item being accepted or rejected and then use these probabilities to calculate the overall probability.
Let's denote:
- (p) as the probability that an item is accepted.
- (q) as the probability that an item is rejected.
a) To find the probability that the entire shipment shall be accepted, we multiply the probability of each item being accepted together since the acceptance of each item is independent:
[ P(\text{Entire shipment accepted}) = p^n ]
where ( n ) is the number of items in the shipment.
b) Similarly, to find the probability that the entire shipment shall be rejected, we multiply the probability of each item being rejected together:
[ P(\text{Entire shipment rejected}) = q^n ]
It's important to note that ( q = 1 - p ), where ( p ) is the probability of acceptance.
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When evaluating a one-sided limit, you need to be careful when a quantity is approaching zero since its sign is different depending on which way it is approaching zero from. Let us look at some examples.
When evaluating a one-sided limit, you need to be careful when a quantity is approaching zero since its sign is different depending on which way it is approaching zero from. Let us look at some examples.
When evaluating a one-sided limit, you need to be careful when a quantity is approaching zero since its sign is different depending on which way it is approaching zero from. Let us look at some examples.
When evaluating a one-sided limit, you need to be careful when a quantity is approaching zero since its sign is different depending on which way it is approaching zero from. Let us look at some examples.
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