Data collected on the yearly registrations for a Six Sigma seminar at the Quality College are shown in the following table:
a. Develop a 3-Year moving average to forecast registrations from year 4 to 12.
b. Estimate demand again for year 4 to 12 with a 3-Year weighted moving average in which
registrations in the most recent years are given a weight of 0.7, and registrations in the other 2
years are each given a weight of 0.15 and 0.15 respectively.
c. Use exponential smoothing with a smoothing constant of 0.4, 0.6 and 0.7 to forecast the
registration at the seminar. To begin the forecast, assume the year 1 forecast is 5,500 people
signing up.
a. What is the MAD?
b. What is the MSE?
c. Which model is best?
d. Graph the actual data and the forecast data of all the above-mentioned models.

An annual marathon covers a route that has a distance of approximately 26 miles. winning times for this marathon are all over 2 hours. the following data are the minutes over 2 hours for the winning male runners over two periods of 20 years each. earlier period 14 12 15 22 13 10 19 13 9 14 20 18 16 20 23 12 18 17 6 13 recent period 7 11 7 14 8 9 11 14 8 7 9 8 7 9 9 9 9 8 10 8 (a) make a stem-and-leaf display for the minutes over 2 hours of the winning times for the earlier period. use two lines per stem. (use the tens digit as the stem and the ones digit as the leaf. enter none in any unused answer blanks. for more details, view how to split a stem.) minutes beyond 2 hours earlier period 0 1 2 (b) make a stem-and-leaf display for the minutes over 2 hours of the winning times for the recent period. use two lines per stem. (use the tens digit as the stem and the ones digit as the leaf. enter none in any unused answer blanks.) minutes beyond 2 hours recent period (c) compare the two distributions. how many times under 15 minutes are in each distribution