Assignment Questions

Question 1:
Wendy’s Happy Homes Inc. manufactures Home Appliances. Monthly sales of Wendy’s Washers and Dryer Sets for a nine-month period were as follows:
MONTH Washer and Dryer Sales
January 490
February 480
March 450
April 500
May 480
June 470
July 490
August 520
September 530
Forecast October sales using:
1) A four-month moving average
2) a six-month moving average
3. Compute the MAD for each forecast method you used.
Actual October sales were 520 units.
4) Which method was the most accurate?
5) Forecast November and December using the method you believe to be the most accurate.

Question 2:
Refer to the gasoline sales time series data in Table below to answer the following (Copy the file to Excel when done submit here)
1. Compute Three- week, four-week and five-week moving averages for the time series.
2. Compute the MSE for Three- week, the four-week and five-week moving average forecasts. (Look over the PowerPoint)
3. Create a new column to show the trend line (y= mx+b) for the table below
4. What appears to be the best number of weeks of past data (three, four, or five) to use in the moving average computation?
5. Plot gasoline sales time series after obtaining the contract with the Vermont state police
6. Plot gasoline sales time series and three-week moving average Forecasts
7. Plot gasoline sales time series and add the trend line to graph

GASOLINE SALES TIME SERIES AFTER OBTAINING THE CONTRACT WITH THE VERMONT STATE POLICE
Week Sale (1000s of Gallons)
1 17
2 21
3 19
4 23
5 18
6 16
7 20
8 18
9 22
10 20
11 15
12 22
13 31
14 34
15 31
16 33
17 28
18 32
19 30
20 29
22 34
21 33

Question 3:
A critically important aspect of customer service in a supermarket is the waiting time for the checkout.
Data were collected in the table below during time period in which a constant number of checkout counters were open. The total number of customers in the store and the waiting times in minutes were recorded.
a) Use Excel to construct the scatter plot.
b) Determine the linear regression equation between number of customers and waiting time include that on the graph
c) Predict the waiting period when there are 20 customers in the store.
d) Show r= coefficient of regression and r2 =coefficient of determination on the graph
1. Copy the following to Excel work and go back copy and paste here in the respond
2. Go to file to Excel, click on Options, select Add-ins
3. select Analysis Tool pack “follow the YouTube https://www.youtube.com/watch?v=mIoS7IRo36c and the link to regression on youtube https://www.youtube.com/watch?v=Cltt47Ah3Q4

Day Customers Time
1 15 1.5
2 18 1.2
3 9 0.8
4 7 0.5
5 19 2
6 30 2.5
7 27 3
8 13 2
9 11 1.7
10 9 0.5
11 21 2
12 35 5.2
13 25 2.3
14 8 0.2
15 16 0.7
16 21 2.5
17 17 1
18 22 3.8
19 16 1.5
20 24 2.8
21 14 1
22 15 1.7
23 21 3
24 27 2.8
25 17 1
26 21 2.5
27 20 2.9
28 31 3.4
29 38 4
30 42 4.8

Question 4: CASE: Scharadin Hotels:
The Scharadin Hotel in San Antonio, Texas, had recently been experiencing a large number of guest complaints due to billing errors. The complaints seem to center around guests disputing charges on their final hotel bill. Guest complaints ranged from extra charges, such as meals or services that were not purchased, to confusion for not being charged at all. Most hotel guests use express checkout on their day of departure. With express checkout the hotel bill is left under the guest’s door in the early morning hours and, if all is in order, does not require any additional action on the guest’s part. Express checkout is a welcome service by busy travelers who are free to depart the hotel at their convenience. However, the increased number of billing errors began creating unnecessary delays and frustration for the guests who unexpectedly needed to settle their bill with the front desk. The hotel staff often had to calm frustrated guests who were rushing to the airport and were aggravated that they were getting charged for items they had not purchased.
Identifying the Source of the Problem
Larraine Scharadin, Milo Scharadin’s niece, had recently been appointed to run the San Antonio hotel. A recent business school graduate, Larraine had grown up in the hotel business. She was poised and confident and understood the importance of high quality for the hotel. When she became aware of the billing problem, she immediately called a staff meeting to uncover the source of the problem. During the staff meeting discussion quickly turned to problems with the new computer system and software that had been put in place. Tim Coleman, head of MIS, defended the system, stating that the system was sound, and the problems were exaggerated. Tim claimed that a few hotel guests made an issue of a few random problems. Scott Schultz, head of operations, was not so sure. Scott said that he noticed that the number of complaints seem to have significantly increased since the new system was installed. He said that he had asked his team to perform an audit of 50 random bills per day over the past 30 days. Scott showed the following numbers to Larraine, Tim, and the other staff members.

Day Number of incorrect bills
1 2
2 2
3 1
4 2
5 2
6 3
7 2
8 2
9 1
10 2
11 1
12 2
13 3
14 3
15 2
16 2
17 2
18 2
19 1
20 3
21 3
22 3
23 3
24 4
25 5
26 5
27 6
28 5
29 5
30 5

Everyone looked at the data that had been presented. Then Tim exclaimed: “Notice that the number of errors increases in the last third of the month. The computer system had been in place for the entire month so that can’t be the problem. Scott, it is probably the new employees you have on staff that are not entering the data properly.” Scott quickly retaliated: “The employees are trained properly! Everyone knows the problem is the computer system!” The argument between Tim and Scott become heated, and Larraine decided to step in. She said,“Scott, I think it is best if you perform some statistical analysis of that data and send us your findings. You know that we want a high-quality standard. We can’t be Motorola with six-sigma quantity, but let’s try for three-sigma. Would you develop some control charts with the data and let us know if you think the process is in control?”

Case Questions
1. Setup three-sigma control limits with the given data and graph it using Excel (Go to the link for help https://www.youtube.com/watch?v=os17KYZAnd0)
Make sure the mean, upper control and lower control Sigma on the graph
2. Is the process in control? Why?
3. Based on your analysis do you think the problem is the new computer system or something else?
4. What advice would you give to Larraine based on the information that you have?