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The mean life of a television set is 138 months with a variance of 324. if a sample of 83 televisions is randomly selected, what is the probability that the sample mean would differ from the true mean by less than 5.4 months?

a) 0.6826
b) 0.8413
c) 0.1587
d) 0.9772

User Akhilesh
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1 Answer

4 votes

Final answer:

To determine the probability that the sample mean differs from the true mean by less than 5.4 months, calculate the Z-score and consult the Z-table. The Z-score is approximately 2.73, leading to a probability of about 0.9967, with the closest answer choice being 0.9772 (option d).

Step-by-step explanation:

The question pertains to the probability that the sample mean of 83 television sets will be within 5.4 months of the true mean life of television sets, given a population mean (μ) of 138 months and a variance (σ2) of 324 months2. First, we calculate the standard deviation (σ) which is the square root of the variance. So, σ = √324 = 18 months. Next, we find the standard error of the mean (SEM), which is given by σ/√n, where n is the sample size. Here, n = 83, making the SEM = 18/√83 ≈ 1.98 months. We now express our range of interest (within 5.4 months of the mean) as a Z-score by dividing by the SEM, yielding 5.4 / 1.98 ≈ 2.73. Using the Z-table, we find that the probability of being within ±2.73 standard deviations of the mean is approximately 0.9967 (98.34% on both sides minus 1.32% beyond both tails = 0.9967). This suggests that the closest answer choice would be 0.9772, corresponding to option d.

User Deasserted
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