Answer:
[tex]\chi^2_{\alpha/2}=43.195[/tex]
[tex]\chi^2_{1- \alpha/2}=14.573[/tex]
b. 14.573 and 43.195.
Step-by-step explanation:
Previous concepts
A confidence interval is "a range of values that’s likely to include a population value with a certain degree of confidence. It is often expressed a % whereby a population mean or variance lies between an upper and lower interval".
The margin of error is the range of values below and above the sample statistic in a confidence interval.
The Chi square distribution is the distribution of the sum of squared standard normal deviates .
2) Solution to the problem
The confidence interval for the population variance is given by the following formula:
[tex]\frac{(n-1)s^2}{\chi^2_{\alpha/2}} \leq \sigma^2 \leq \frac{(n-1)s^2}{\chi^2_{1-\alpha/2}}[/tex]
We need on this case to calculate the critical values. First we need to calculate the degrees of freedom given by:
[tex]df=n-1=28-1=27[/tex]
Since the Confidence is 0.95 or 95%, the value of [tex]\alpha=1-0.95=0.05[/tex] and [tex]\alpha/2 =0.025[/tex], and we can use excel, a calculator or a table for the Chis square distribution with 27 degrees of freedom to find the critical values. We need a value that accumulates 0.025 of the area on the left tail and 0.025 of the area on the right tail.
The excel commands would be: "=CHISQ.INV(0.025,27)" "=CHISQ.INV(0.975,27)". so for this case the critical values are:
[tex]\chi^2_{\alpha/2}=43.195[/tex]
[tex]\chi^2_{1- \alpha/2}=14.573[/tex]
b. 14.573 and 43.195.