If n=25 and the sample standard deviation is 15, construct a 95% confidence interval for the true standard deviation. (Assume the population is approximately Normal).
The confidence interval is used to estimate the population parameter with the help of a sample statistic. The confidence interval of population standard deviation is computed by
"\\sqrt{ \\frac{(n-1)s^2}{\u03c7^2_{\u03b1\/2}} } < \\sigma < \\sqrt{\\frac{(n-1)s^2}{\u03c7^2_{1-\u03b1\/2}} }"
where n is the sample size, and s is the sample standard deviation.
The values "\u03c7^2_{1-\u03b1\/2}" and "\u03c7^2_{\u03b1\/2}" are critical values corresponding to the left tail and right tail area α/2 respectively. The value of α/2 is computed by
"\\frac{\u03b1}{2}= \\frac{1}{2}(1- \\frac{CL}{100})"
The degree of freedom for this distribution is given by
df=n-1
The confidence level is 95%. So, to find the value of α/2 , substitute 95% for CL in
"\\frac{\u03b1}{2}= \\frac{1}{2}(1- \\frac{CL}{100}) \\\\\n\n\\frac{\u03b1}{2}= \\frac{1}{2}(1- \\frac{95}{100}) \\\\\n\n= \\frac{1}{2}(1-0.95) \\\\\n\n= \\frac{0.05}{2} \\\\\n\n= 0.025"
The sample size is 25, so the degree of freedom will be 24.
Using the technology or table of chi-square distribution, the critical value corresponding to the left tail area 0.025 is 12.401 and the critical value corresponding to the right tail area is 39.365.
To find the 95% confidence interval of population standard deviation, substitute
"s= 15 \\\\\n\nn=25 \\\\\n\n\u03c7^2_{\u03b1\/2} = 39.365 \\\\\n\n\u03c7^2_{1-\u03b1\/2} = 12.401"
in
"\\sqrt{ \\frac{(n-1)s^2}{\u03c7^2_{\u03b1\/2}} } < \\sigma < \\sqrt{\\frac{(n-1)s^2}{\u03c7^2_{1-\u03b1\/2}} } \\\\\n\n\\sqrt{ \\frac{(25-1)15^2}{39.365 }} < \\sigma < \\sqrt{\\frac{(25-1)15^2}{12.401 }} \\\\\n\n\\sqrt{ \\frac{24.225}{39.365 }} < \\sigma < \\sqrt {\\frac{24.225}{12.401 }} \\\\\n\n\\sqrt{ 137.177}< \\sigma < \\sqrt {435.45}\\\\\n\n11.71 < \\sigma < 20.87"
So, the 95% confidence interval for population standard deviation is (11.71, 20.87).
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