Question
MGMT2026 - Production & Operations Management-UWI QUESTIONS ON FORECASTING Mark Gershon, owner of a musical instrument distributorship, thinks that demand for guitars may be related
MGMT2026 - Production & Operations Management-UWI
QUESTIONS ON FORECASTING
- Mark Gershon, owner of a musical instrument distributorship, thinks that demand for guitars may be related to the
number of television appearances by the popular group Maroon 5 during the previous month. Mark has collected the data shown in the following table:
Demand for Guitars | 3 | 6 | 7 | 5 | 10 | 7 |
Maroon 5 TV Appearances | 3 | 4 | 7 | 6 | 8 | 5 |
- Graph these data to see whether a linear equation might describe the relationship between the group's television shows and guitar sales.
- Use the least-squares regression method to derive a forecasting equation.
- Use the least-squares regression method to derive a forecasting equation.
- What is your estimate for guitar sales if Maroon 5 performed on TV nine times last month?
Weekly sales of copy paper at Cubicle Suppliers are provided in the table below. Compute a three-period moving average and a four-period moving average for weeks 5, 6, and 7. Compute the MAD for both forecasting methods. Which model is more accurate? Forecast week 8 with the more accurate method.
Week Sales (cases)
1 17
2 21
3 27
4 31
5 19
6 17
7 21
2. Sales for refrigerators are given in the table below. Using a 3-month moving average, forecast sales for February the following year. Calculate the MAD for this model.
3-Month | Absolute | ||
Month | Sales | Moving Average | Deviation |
January | 11 | ||
February | 14 | ||
March | 16 | ||
April | 10 | ||
May | 15 | ||
June | 17 | ||
July | 11 | ||
August | 14 | ||
September | 17 | ||
October | 12 | ||
November | 14 | ||
December | 16 | ||
January | 11 | ||
February |
Use the weighted moving average to forecast sales for February the following year . Calculate the MAD for this model.
Which model is better?
Month | Sales | 3-Month Weighted Moving Average | Absolute Deviation |
January | 11 | ||
February | 14 | ||
March | 16 | ||
April | 10 | ||
May | 15 | ||
June | 17 | ||
July | 11 | ||
August | 14 | ||
September | 17 | ||
October | 12 | ||
November | 14 | ||
December | 16 | ||
January | 11 | ||
February |
3. Dr. Lillian Sam, a New Orleans psychologist, specializes in treating patients who are agoraphobic (i.e., afraid to leave their homes). The following table indicates how many patients Dr. Sam has seen each year for the past 10 years. It also indicates what the robbery rate was in New Orleans during the same year:
Crime | Patients | ||||||||||||
Year | Rate X | Y | |||||||||||
1 | 58.3 | 36 | |||||||||||
2 | 61.1 | 33 | |||||||||||
3 | 73.4 | 40 | |||||||||||
4 | 75.7 | 41 | |||||||||||
5 | 81.1 | 40 | |||||||||||
6 | 89.0 | 55 | |||||||||||
7 | 101.1 | 60 | |||||||||||
8 | 94.8 | 54 | |||||||||||
9 | 103.3 | 58 | |||||||||||
10 | 116.2 | 61 | |||||||||||
Column totals | 854.0 | 478 |
Using trend (linear regression) analysis, predict the number of patients Dr. Sam will see in years 11 and 12 as a function of time.
4. The following gives the number of pints of type B blood used at Woodlawn Hospital in the past 6 weeks:
Week of | Pints used |
August 31 | 360 |
September 7 | 389 |
September 14 | 410 |
September 21 | 381 |
September 28 | 368 |
October 5 | 374 |
October 12 |
Forecast the demand for the week of October 12 using
5. Sales of Volkswagen's popular Beetle have grown steadily at auto dealerships in Nevada during the past 5 years (see table below). The sales manager had predicted before the new model was introduced that first year sales would be 410 VWs. Using exponential smoothing with a weight of =.30, develop forecasts for years 2 through 6.
Forecast Exponential | Absolute | ||
Year | Sales | Smoothing a = 0.6 | Deviation |
1 | 450 | 410.0 | |
2 | 495 | ||
3 | 518 | ||
4 | 563 | ||
5 | 584 | ||
6 | |||
| |||
| |||
Forecast Exponential | Absolute | ||
Year | Sales | Smoothing a = 0.9 | Deviation |
1 | 450 | 410.0 | |
2 | 495 | ||
3 | 518 | ||
4 | 563 | ||
5 | 584 | ||
6 | |||
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