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Answer :
To find the 99% confidence interval for the mean high temperature of the towns, we'll follow these steps:
1. Collect the Sample Data:
The high temperatures recorded for the 10 small towns are:
- 97.5, 96.5, 99.1, 99.5, 98.2, 99.7, 96.7, 97.0, 97.1, 99.6
2. Calculate the Sample Mean:
The sample mean is calculated by summing all the temperatures and dividing by the sample size (10).
[tex]\[
\text{Sample Mean} = \frac{97.5 + 96.5 + 99.1 + 99.5 + 98.2 + 99.7 + 96.7 + 97.0 + 97.1 + 99.6}{10} = 98.09
\][/tex]
3. Calculate the Sample Standard Deviation:
The sample standard deviation is a measure of the amount of variation or dispersion in a set of values. It accounts for n-1 degrees of freedom for a sample.
- This calculation gives us a sample standard deviation of approximately 1.29.
4. Calculate the Standard Error:
The standard error (SE) is calculated by dividing the standard deviation by the square root of the sample size.
[tex]\[
\text{Standard Error} = \frac{1.29}{\sqrt{10}} \approx 0.41
\][/tex]
5. Find the Critical Value:
For a 99% confidence interval, we need the critical value associated with this confidence level. Using the standard normal distribution, the critical value (z-score) is approximately 2.576.
6. Calculate the Margin of Error:
The margin of error is the product of the critical value and the standard error.
[tex]\[
\text{Margin of Error} = 2.576 \times 0.41 \approx 1.05
\][/tex]
7. Determine the Confidence Interval:
Using the sample mean and the margin of error, we determine the confidence interval by adding and subtracting the margin of error from the sample mean.
- Lower limit: [tex]\( 98.09 - 1.05 = 97.04 \)[/tex]
- Upper limit: [tex]\( 98.09 + 1.05 = 99.14 \)[/tex]
Therefore, the 99% confidence interval for the mean high temperature of the towns is [tex]\((97.04, 99.14)\)[/tex].
1. Collect the Sample Data:
The high temperatures recorded for the 10 small towns are:
- 97.5, 96.5, 99.1, 99.5, 98.2, 99.7, 96.7, 97.0, 97.1, 99.6
2. Calculate the Sample Mean:
The sample mean is calculated by summing all the temperatures and dividing by the sample size (10).
[tex]\[
\text{Sample Mean} = \frac{97.5 + 96.5 + 99.1 + 99.5 + 98.2 + 99.7 + 96.7 + 97.0 + 97.1 + 99.6}{10} = 98.09
\][/tex]
3. Calculate the Sample Standard Deviation:
The sample standard deviation is a measure of the amount of variation or dispersion in a set of values. It accounts for n-1 degrees of freedom for a sample.
- This calculation gives us a sample standard deviation of approximately 1.29.
4. Calculate the Standard Error:
The standard error (SE) is calculated by dividing the standard deviation by the square root of the sample size.
[tex]\[
\text{Standard Error} = \frac{1.29}{\sqrt{10}} \approx 0.41
\][/tex]
5. Find the Critical Value:
For a 99% confidence interval, we need the critical value associated with this confidence level. Using the standard normal distribution, the critical value (z-score) is approximately 2.576.
6. Calculate the Margin of Error:
The margin of error is the product of the critical value and the standard error.
[tex]\[
\text{Margin of Error} = 2.576 \times 0.41 \approx 1.05
\][/tex]
7. Determine the Confidence Interval:
Using the sample mean and the margin of error, we determine the confidence interval by adding and subtracting the margin of error from the sample mean.
- Lower limit: [tex]\( 98.09 - 1.05 = 97.04 \)[/tex]
- Upper limit: [tex]\( 98.09 + 1.05 = 99.14 \)[/tex]
Therefore, the 99% confidence interval for the mean high temperature of the towns is [tex]\((97.04, 99.14)\)[/tex].
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