In this exercise, we will draw samples from the large "population" (in blue) in order to estimate the true average; The random numbers in column A can be used to pick a random sample. Follow the instructions and fill in the green boxes on the 95% and 80% confidence level tabs. Step 1: Sort the data on the left by highlighting columns A and B and choosing Data>Sort>Sort By Column A Step 2: Highlight the first 15 data points (blue column) and paste them into the greeen boxes below: Step 3: Calculate the sample mean (=average()), the sample standard deviation (=stdev.s()), the sample size (=count()), xbar = t= s= n= and the t multiplier (=t.inv()) Step 4: Calculate a 95% confidence interval for the average. Do NOT use =confidence! Use the formula for the confidence interval. Lower Bound: xbar - t*s/sqrt(n) Upper Bound: xbar + t*s/sqrt(n) Lower: Upper: Step 5: Does your sample confidence interval include the actual population average? How often do you expect it would work out the way it did? How could you check that? Step 1: Sort the data on the left by highlighting columns A and B and choosing Data>Sort>Sort By Column A Step 2: Highlight the first 15 data points (blue column) and paste them into the greeen boxes below: Step 3: Calculate the sample mean (=average()), the sample standard deviation (=stdev.s()), the sample size (=count()), xbar = t= s= n= and the t multiplier (=t.inv()) Step 4: Calculate an 80% confidence interval for the average. Do NOT use =confidence! Use the formula for the confidence interval. Lower Bound: xbar - t*s/sqrt(n) Upper Bound: xbar + t*s/sqrt(n) Lower: Upper: Step 5: Does your sample confidence interval include the actual population average? How often do you expect it would work out the way it did? How could you check that