2. Copy and paste the code above and modify it to produce a 95%-confidence interval for o. . Change xbar to s. . On Line 11, change mean () to the appropriate command for standard deviation. . Add a histogram for (n - 1)82 where so = 80 . s. sorted[left] and s. sorted [right] are bounds for s, not o. In order to find the bounds for we observe that xi = (n - 1)s where s = s. sorted[left] XR = (n - 1)sh where sp = s. sorted [right]. So the bounds for o is(See Worksheet #8) n - n - Xi SR SL . You can find the theoretical values for x} and x} as xi = qchisq(a/2, df = degrees of freedom), x1 = qchisq(1 - a/2, df = degrees of freedom) Then, compute the lower and the upper bounds for o as in the previous step. . Run the code and observe that the distribution of s is skewed (asymmetric) as for the x3 distri- bution. Also the numerical result for the confidence interval should match the theoretical result within a relatively small error