Step 1 :The problem involves constructing a 99% confidence interval for the population variance and standard deviation. The sample size is 30 and the sample standard deviation is $3429.
Step 2 :We use the chi-square distribution to construct the confidence interval for the population variance. The formula for the confidence interval is given by: \[\left( \frac{(n-1)s^2}{\chi^2_{\alpha/2, n-1}}, \frac{(n-1)s^2}{\chi^2_{1-\alpha/2, n-1}} \right)\] where n is the sample size, s is the sample standard deviation, and \(\chi^2_{\alpha/2, n-1}\) and \(\chi^2_{1-\alpha/2, n-1}\) are the chi-square values for the degrees of freedom (n-1) and significance level \(\alpha\) (in this case, \(\alpha = 0.01\) for a 99% confidence interval).
Step 3 :Substituting the given values into the formula, we get the chi-square values as 13.12114888796041 and 52.335617785933614.
Step 4 :Using these chi-square values, we calculate the lower and upper bounds of the confidence interval for the population variance as 6515317.931178544 and 25987296.68503925 respectively.
Step 5 :Rounding these values to the nearest integer, we get the final answer. The 99% confidence interval for the population variance is approximately \(\boxed{(\$6,515,318, \$25,987,297)}\). This means that we are 99% confident that the true population variance lies within this interval.