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(b) An electronics company manufactures resistors that have a mean resistance of 100 ohms and a standard deviation of 10 ohms. The distribution of resistance is normal. Find the probability that a random sample of n = 75 resistors will have an average of fewer than 95 ohms. Given that P(Z > 2.5)?
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(b) An electronics company manufactures resistors that have a mean res...
Calculating the Probability of Average Resistance
To find the probability that a random sample of 75 resistors will have an average resistance of fewer than 95 ohms, we need to use the Central Limit Theorem since the sample size is large (n = 75).

Step 1: Calculate the Standard Error
The standard error (SE) of the mean is calculated using the formula:
SE = σ / sqrt(n)
where σ is the standard deviation and n is the sample size.
In this case, σ = 10 ohms and n = 75 resistors. So, SE = 10 / sqrt(75) ≈ 1.15 ohms.

Step 2: Find the Z-score
Next, we calculate the Z-score using the formula:
Z = (X̄ - μ) / SE
where X̄ is the sample mean, μ is the population mean, and SE is the standard error.
Given that μ = 100 ohms and X̄ = 95 ohms, we get:
Z = (95 - 100) / 1.15 ≈ -4.35

Step 3: Find the Probability
Now, we need to find the probability that Z > 2.5. Since the Z-score we calculated (-4.35) is much lower than 2.5, the probability of having an average resistance of fewer than 95 ohms is very close to 0.
Therefore, the probability that a random sample of 75 resistors will have an average resistance of fewer than 95 ohms is extremely low, given that P(Z > 2.5) is so small.
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(b) An electronics company manufactures resistors that have a mean resistance of 100 ohms and a standard deviation of 10 ohms. The distribution of resistance is normal. Find the probability that a random sample of n = 75 resistors will have an average of fewer than 95 ohms. Given that P(Z > 2.5)?
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