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Forecasting Methods - Introduction to Operations Management - Quiz, Exercises of Production and Operations Management

Forecasting Methods, Demand Pattern, Performance Measure, Cancel Out Forecasts, Fish Exercise, Qualitative Model of Forecasting, Delphi Technique, Time Series Model, Causal Model, Compute Forecasts.These are the important points of Operations Management.

Typology: Exercises

2012/2013

Uploaded on 01/01/2013

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Quiz
Multiple Choice Questions (1 pt. each)
1. Which of the following forecasting methods would be best for the following demand pattern?
100
105
110
115
0 10 20 30 40 50
a. LP
b. Average
c. SMA – 2
d. SMA – 5
e. SES
f. DES
g. TES
2. Which of the following forecasting methods would be best for the following demand pattern?
95
100
105
110
115
120
125
130
0 20 40 60 80 100 120
a. LP
b. Average
c. SMA – 2
d. SMA – 5
e. SES
f. DES
g. TES
3. Which performance measure allows forecasts that are too low to cancel out forecasts that are too
high?
a. Bias
b. MAD
c. MAPE
d. MSE
e. SE
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Quiz

Multiple Choice Questions (1 pt. each)

  1. Which of the following forecasting methods would be best for the following demand pattern?

100

105

110

115

0 10 20 30 40 50 a. LP b. Average c. SMA – 2 d. SMA – 5 e. SES f. DES g. TES

  1. Which of the following forecasting methods would be best for the following demand pattern?

95

100

105

110

115

120

125

130

0 20 40 60 80 100 120 a. LP b. Average c. SMA – 2 d. SMA – 5 e. SES f. DES g. TES

  1. Which performance measure allows forecasts that are too low to cancel out forecasts that are too high? a. Bias b. MAD c. MAPE d. MSE e. SE

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  1. In the fish exercise (HW1) we used the following equation to predict fish populations

PAug = PApr + (a – (b ×××× PApr)) ×××× PApr) This is an example of a: a. SLR b. A qualitative model of forecasting. c. The Delphi technique d. A time series model of forecasting. e. A causal model of forecasting.

Forecasting number of tourist visits to Alberta

The “Data” worksheet shows the number of tourists from Japan that visited Alberta from the first quarter of 2001 to the first quarter of 2004. The data are in thousands of tourists and your answers should be in thousands of tourists as well, i.e., do not multiply the numbers by 1,000.

Imagine that the current date is April 15, 2004. You work for Alberta Tourism and you have been asked to forecast the number of tourists from Japan during the next few quarters.

  1. (2 pts) Use the WMA method with a window size of 3. One of the weights should be 0.5 and one should be 0.3. Forecast the number of tourists for all quarters that you can, up to the third quarter of
    1. Compute MAD for this method, using all quarters for which you have forecast errors.

The “TES” worksheet has been laid out for you. The parameters LS, TS, and SS have all been set. Do not change these parameters.

  1. (2 pts) Report the most recent seasonality index for quarter 4.
  2. (3 pts) Use TES to compute forecasts for quarter 2, 2004 to quarter 2, 2005.
  3. (2 pts) Report the SE using all quarters for which you have forecast errors.
  4. (2 pt) Your boss informs you that, due to global warming and a new advertising campaign, each quarter will see a deseasonalized increase over the previous quarter of, on the average, 3 (thousand) tourists. This will start with quarter 2, 2004. He wants to know the new forecasts for quarter 2, 2004 to quarter 2, 2005.

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