Use technology to construct the confidence intervals for the population variance o2 and the population standard deviation o. Assume the sample is taken from a normally distributed population.
Use technology to construct the confidence intervals for the population variance o2 and the population standard deviation o. Assume the sample is taken from a normally distributed population.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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![**Educational Content: Constructing Confidence Intervals for Population Variance**
In this example, we are tasked with constructing confidence intervals for the population variance (σ²) and the population standard deviation (σ) using technology. It is important to assume that the sample is drawn from a normally distributed population.
**Given Information:**
- Confidence level (c): 0.99
- Sample variance (s²): 8.41
- Sample size (n): 30
To construct the confidence interval for the population variance, follow these steps:
1. **Identify the Chi-Square Distribution:**
The degrees of freedom (df) are calculated as n - 1. In this case, df = 30 - 1 = 29.
2. **Determine the Chi-Square Critical Values:**
Using a chi-square distribution table or technology, find the chi-square values that correspond to the confidence level of 0.99 with 29 degrees of freedom. These values represent the lower (χ²L) and upper (χ²U) critical points.
3. **Calculate the Confidence Interval:**
The confidence interval for the population variance is calculated using the formula:
\[
\left(\frac{(n-1) \cdot s²}{χ²U}, \frac{(n-1) \cdot s²}{χ²L}\right)
\]
**Task:**
Complete the calculation and fill in the blanks for the confidence interval, rounding to two decimal places as needed.
The result will provide an interval within which we are 99% confident the true population variance lies.
**Note:** This procedure assumes the sample data comes from a population that follows a normal distribution, a critical assumption when using chi-square distribution-based methods.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fffe5e6f1-d5fb-4a9c-adda-cf80907eb9e9%2F6325e1bc-7b29-4c84-b9c9-0f201415761c%2Fa5pd3fd.jpeg&w=3840&q=75)
Transcribed Image Text:**Educational Content: Constructing Confidence Intervals for Population Variance**
In this example, we are tasked with constructing confidence intervals for the population variance (σ²) and the population standard deviation (σ) using technology. It is important to assume that the sample is drawn from a normally distributed population.
**Given Information:**
- Confidence level (c): 0.99
- Sample variance (s²): 8.41
- Sample size (n): 30
To construct the confidence interval for the population variance, follow these steps:
1. **Identify the Chi-Square Distribution:**
The degrees of freedom (df) are calculated as n - 1. In this case, df = 30 - 1 = 29.
2. **Determine the Chi-Square Critical Values:**
Using a chi-square distribution table or technology, find the chi-square values that correspond to the confidence level of 0.99 with 29 degrees of freedom. These values represent the lower (χ²L) and upper (χ²U) critical points.
3. **Calculate the Confidence Interval:**
The confidence interval for the population variance is calculated using the formula:
\[
\left(\frac{(n-1) \cdot s²}{χ²U}, \frac{(n-1) \cdot s²}{χ²L}\right)
\]
**Task:**
Complete the calculation and fill in the blanks for the confidence interval, rounding to two decimal places as needed.
The result will provide an interval within which we are 99% confident the true population variance lies.
**Note:** This procedure assumes the sample data comes from a population that follows a normal distribution, a critical assumption when using chi-square distribution-based methods.
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