Saint leo MBA550 module 3 assignment

2. The manger of the Carpet City outlet needs to make an accurate forecast of the demand of Soft Shag carpet (its biggest seller). If the manger does not order enough carpet from the carpet mill, customer will their carpet from one of Carpet City's many competitors. The manager has collected the following demand data for the past 8 months:

Demand for Soft Shag
Month Carpet (1,000 yd.)
1 8
2 12
3 7
4 9
5 15
6 11
7 10
8 12

a. Compute a 3- month moving average forecast for months 4 through 9.
b. Compute a weighed 3- month moving average forecast for months 4 through 9. Assign weights of .55, .33, and .12 to the months in sequence, starting with the most recent month.
c. Compare the two forecasts by using MAD. Which forecast appears to be more accurate?

6. The manager of the Petroco Service station wants to forecast the demand for unleaded gasoline next month so that the proper number of gallons can be ordered from the distributor. The owner has accumulated the following data on demand for unleaded gasoline from sales during the past 10 months:
Month Gasoline Demand (gal)
October 800
November 725
December 630
January 500
February 645
March 690
April 730
May 810
June 1200
July 980

a. Compute and exponentially smoothed forecast, using on α value of .30.
b. Compute an adjusted exponentially smoothed forecast (with α =.30 and β=.20).
c. Compare the two forecast by using MAPD and indicate which seems to be more accurate.

Problem 4-38

Apperson and Fitz is a chain of clothing stores that caters to high school and college students. It publishes a quarterly catalog and operates a Web site that features provocatively attired males and females. The Web site is very expensive to maintain, and company executives are not sure whether the number of hits at the site relate to sales (i.e., people may be looking at the site's pictures only). The Web master has accumulated the following data for hits per month and orders placed at the Web site for the past 20 months:

Month Hits(1,000s) Orders(1,000s)
1 34.2 7.6
2 28.5 6.3
3 36.7 8.9
4 42.3 5.7
5 25.8 5.9
6 52.3 6.3
7 35.2 7.2
8 27.9 4.1
9 31.4 3.7
10 29.4 5.9
11 46.7 10.8
12 43.5 8.7
13 52.6 9.3
14 61.8 6.5
15 37.3 4.8
16 28.9 3.1
17 26.4 6.2
18 39.4 5.9
19 44.7 7.2
20 46.3 5.5

Develop a liner regression model for these data and indicate whether there appears to be a strong relationship between Web site hits and orders. What would be the forecast for orders with 50,000 hits per month?