1. Find the missing value (A) in the table (you may also want to manually calculate a few of the other given values to ensure that you know how the calculations are done). You can report the value that you found to your discussion board, and if anyone is having trouble with this exercise, you can help each other (on the discussion board) and describe how you arrived at your result. Also, what does the value represent, and what does the resulting number mean in words? (e.g., It is the seasonal factor for..., and the result of ... means that...).

2. Find the average seasonal factor for each four seasons (days). Report your result for Sunday.

3. Make a forecast for Sunday of year 6 if total attendance in year 6 is forecast to be 10,000. Report your result; help others (or ask for help) as needed.

4. One of the organizers has questioned the wisdom of giving equal weighting to all five past years (when calculating the average seasonal factors) and has proposed that only the three most recent years be used, with the most recent year being weighted by 0.5 and the other two by 0.25. Discuss your thoughts on this suggestion. (You may also wish to calculate and compare average seasonal factors and forecasts for year six under each method using all five years, or only using the most recent three years and weighting them as proposed).

Daily attendance for past five years Year 1 Year 2 Year 3 Year 4 Thurs 1,03 1,028 1,300 1.296 Fri 2,347 2,429 2,522 2,720 Sat 2.908 2,859 2,958 3,010 Sunday! 2.635 2.678 2.729 2.532 TOTAL 9,313 9,394 9,509 9,558 Year 5 1,363 2,806 3,201 2.449 9,819 Seasonal indexes Year 1 Year 2 Thurs 0.61 0.61 Fri 1.01 1.03 Sat 1.25 1.22 Sunday 1.13 1.14 Year 3 0.55 1.06 1.24 1.15 Year 4 0.54 1.14 1.26 1.06 Year 5 0.56 A 130 1.00 3,500 3,000 2,500 2,000 1,500 1,000 Thurs Fri Sat Sunday -Year -Year2-Year 3-Year 4 -Years