Statistics: sample mean of normal distribution

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  • #1
musicmar
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Homework Statement


The diameter of a shaft in an optical storage drive is normally distributed N(μ,σ2). The drive specifies that the shaft be 0.2500 ± 0.0015 in. Suppose μ= 0.2508 in and σ = 0.0005 in. What fraction of shafts conform to the design specifications?


The Attempt at a Solution


I am confused with the terminology of this problem. Is 0.2500 the population mean and 0.2508 is the sample mean?
Or is this completely unrelated, and I have to find the probability that a length be between 0.2485 and 0.2515 in?
Some help in getting started would be appreciated.
Thank you!
 
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  • #2
musicmar said:

Homework Statement


The diameter of a shaft in an optical storage drive is normally distributed N(μ,σ2). The drive specifies that the shaft be 0.2500 ± 0.0015 in. Suppose μ= 0.2508 in and σ = 0.0005 in. What fraction of shafts conform to the design specifications?

The Attempt at a Solution


I am confused with the terminology of this problem. Is 0.2500 the population mean and 0.2508 is the sample mean?
Or is this completely unrelated, and I have to find the probability that a length be between 0.2485 and 0.2515 in?
Some help in getting started would be appreciated.
Thank you!

It is crystal clear from the wording that your second interpretation is the correct one. (When I say crystal clear I mean: don't read more into the problem than what it says.)

RGV
 
Last edited:

Related to Statistics: sample mean of normal distribution

1. What is the normal distribution?

The normal distribution is a probability distribution that is commonly seen in nature and many real-world phenomena. It is a bell-shaped curve that is symmetrical around the mean and is characterized by its mean and standard deviation.

2. How is the sample mean of a normal distribution calculated?

The sample mean of a normal distribution is calculated by taking the sum of all the values in the sample and dividing it by the total number of values in the sample. This is also known as the arithmetic mean.

3. Why is the sample mean an important measure in statistics?

The sample mean is an important measure in statistics because it provides a central value that represents the entire sample. It is also used to make inferences about the population mean, which is often unknown.

4. What does the sample mean represent in a normal distribution?

The sample mean represents the average value of the sample in a normal distribution. It is the point where the curve is at its highest and is also the same as the mean of the population, assuming the sample is representative of the population.

5. How does the sample size affect the accuracy of the sample mean in a normal distribution?

The sample size has a direct impact on the accuracy of the sample mean in a normal distribution. As the sample size increases, the sample mean becomes a more reliable estimate of the population mean. This is because with a larger sample, there is less variability and a smaller margin of error.

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