Step 1 :Given values are: sample size \(n = 22\), sample standard deviation \(s = 4.6\), and level of significance \(\alpha = 0.10\).
Step 2 :First, calculate the sample variance \(s^2 = s^2 = 21.16\).
Step 3 :Next, calculate the critical values from the Chi-Square distribution. The lower critical value \(\chi^2_{lower} = 11.59\) and the upper critical value \(\chi^2_{upper} = 32.67\).
Step 4 :Substitute these values into the formula to get the confidence interval for the population variance. The lower confidence interval \(CI_{lower} = 13.60\) and the upper confidence interval \(CI_{upper} = 38.34\).
Step 5 :The confidence interval for the population variance \(\sigma^2\) is between 13.6 and 38.3. This means that we are 90% confident that the true population variance lies within this interval.
Step 6 :Final Answer: The confidence interval for the population variance \(\sigma^2\) is \(\boxed{[13.6, 38.3]}\).