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The volume in a set of wine bottles is known to follow a normal distribution with a mean of [tex]\mu[/tex] ounces and a standard deviation of [tex]\sigma = 0.5[/tex] ounces. You take a sample of the bottles and measure their volumes. How many bottles do you need to sample to construct a 90% confidence interval for [tex]\mu[/tex] with a margin of error of at most 0.1 ounces?

Answer :

We need to sample at least 18 wine bottles to construct a 90% confidence interval for the mean volume of the population, with a margin of error of at most 0.1 ounces.

To determine the sample size required for a given confidence interval and margin of error, we need to use the following formula:

[tex]n = (Z^2 * \sigma^2) / E^2[/tex]

Where:

n = sample size

Z = the z-score associated with the desired confidence interval (for 90% confidence, Z = 1.645)

σ = the standard deviation of the population (0.5 ounces in this case)

E = the desired margin of error (0.1 ounces in this case)

Plugging in the values, we get:

[tex]n = (1.645^2 * 0.5^2) / 0.1^2[/tex]

n = 17.1

Thus, we need to sample at least 18 wine bottles to create a 90% confidence interval for the population's mean volume, with a margin of error of no more than 0.1 ounces.

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Rewritten by : Barada

We need to sample at least 69 bottles to construct a 90% confidence interval for the mean volume of the wine bottles with a margin of error at most 0.1 ounces.

We have,

To construct a confidence interval for the mean volume of the wine bottles, we need to use the formula:

Confidence interval = sample mean ± margin of error

Where,

Margin of error = z (σ/√(n))

Here, we want to construct a 90% confidence interval with a margin of error at most 0.1 ounces.

This means that the margin of error should be less than or equal to 0.1, and the confidence level is 90%, so the critical value of z is 1.645

(using a standard normal table or calculator).

We are given that the standard deviation is σ = 0.5 ounces.

We don't know the sample mean or the sample size (number of bottles), so we'll use the worst-case scenario to find the sample size that gives the largest margin of error.

The worst-case scenario is when the sample mean is equal to the population mean (μ) plus the margin of error (0.1 ounces), and the sample size is as small as possible (which gives the largest margin of error).

So, we have:

0.1 = 1.645 x (0.5/sqrt(n))

Solving for n, we get:

n = (1.645 x 0.5/0.1)²

n = 68.225

Rounding up to the nearest whole number, we get:

n = 69

Therefore,

We need to sample at least 69 bottles to construct a 90% confidence interval for the mean volume of the wine bottles with a margin of error at most 0.1 ounces.

Learn more about confidence intervals here:

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