Math Problem Statement
A pharmaceutical company receives large shipments of aspirin tablets. The acceptance sampling plan is to randomly select and test 45 tablets, then accept the whole batch if there is only one or none that doesn't meet the required specifications. If one shipment of 7000 aspirin tablets actually has a 4% rate of defects, what is the probability that this whole shipment will be accepted? Will almost all such shipments be accepted, or will many be rejected? Question content area bottom Part 1 The probability that this whole shipment will be accepted is enter your response here.
Solution
We can approach this problem using the binomial distribution, which is ideal when we are dealing with a fixed number of trials (45 in this case), two possible outcomes for each trial (defective or not defective), and a constant probability of success (4% defect rate).
Let's define the variables:
- : number of tablets selected and tested
- : probability that a tablet is defective
- : probability that a tablet is not defective
- : the number of defective tablets in the sample of 45
The sampling plan states that the shipment is accepted if there is one or none defective tablet, i.e., .
We need to calculate , the probability of getting at most 1 defective tablet in the sample.
Step 1: Binomial probability formula
The probability of getting exactly defective tablets out of is given by the binomial probability formula:
Where is the binomial coefficient .
Step 2: Calculate and
-
For (no defective tablets):
-
For (exactly one defective tablet):
Step 3: Find
Now we sum the probabilities of getting 0 or 1 defective tablet:
Conclusion
The probability that the shipment will be accepted is approximately 0.357, or 35.7%.
Interpretation
Since the probability of acceptance is only about 35.7%, many such shipments will likely be rejected.
Would you like further details on any part of the solution? Here are some related questions:
- What is the binomial distribution, and why is it used here?
- How does the probability change if the sample size or defect rate changes?
- What other statistical distributions could be used for similar problems?
- What is the role of the binomial coefficient in these calculations?
- How could we calculate the probability of getting more than one defective tablet?
Tip: Always check if conditions match for using the binomial distribution, such as independent trials and a constant probability of success.
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Math Problem Analysis
Mathematical Concepts
Probability
Binomial Distribution
Formulas
Binomial probability formula: P(X = k) = C(n, k) * p^k * (1-p)^(n-k)
Binomial coefficient: C(n, k) = n! / (k!(n-k)!)
P(X ≤ 1) = P(X = 0) + P(X = 1)
Theorems
Binomial Distribution Theorem
Suitable Grade Level
Undergraduate or Advanced High School (Grades 11-12)
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