6. Interval estimation of the population variance An investigation conducted by a reporter from The New York Times revealed an inverse relationship between prices and temperature in Manhattan retail stores during the summer: High-end retailers tend to set their air conditioning at colder temperatures than low-end retailers. The data set collected by the reporter is displayed as follows, with stores arranged in ascending order based on their temperature measurements. Retail Store Price Point Category Temperature (Degrees Fahrenheit) Bergdorf Goodman Designer 58.3 Hermes Designer 68.6 Tiffany & Co. Designer 70.3 Bloomingdale's Designer 70.8 Macy's Better 73.1 Club Monaco Better 74.0 National Wholesale Liquidators Discount 76.6 Levi's Popular 76.8 Old Navy Popular 80.3 (Data source: Salkin, A. (2005, June 26). Shivering for luxury. The New York Times.) The sample variance for the temperature measurements is $- = 16.865. Assume that summer temperatures inside Manhattan retail stores are normally distributed and that the reporter's sample is a random sample. If you want to develop a 95% confidence interval estimator for the population variance, you will use a s-statistic . with 8 degrees of freedom.Select a Distribution Distributions 0 1 2 3 Use the Distributions tool to develop a 95% confidence interval estimator for the population variance. (Note: Remember to set the degrees of freedom, if applicable.) The 95% confidence interval estimator for the population variance of is: LCL = and UCL =