Question 1

Which of the following statements is/are true about time-series forecasting?
A)The basic strategy is to identify the magnitude and form of each component based on available past data.
B)It is used to make detailed analyses of past demand patterns over time and to project these patterns forward into the future.
C)Demand can be divided into components such as average level,trend,seasonality,cycle and error.
D)All of the above

Accepted Answer

All of the statements mentioned above are true about time-series forecasting. The basic strategy involves identifying the various components of demand, such as average level, trend, seasonality, cycle, and error, based on past data. This helps in making projections about future demand patterns. Time-series forecasting is widely used for analyzing demand patterns and making business decisions based on these patterns.

Question 2

When should qualitative methods NOT be used?
A)When historic data are unreliable
B)When it is impossible to obtain historic data
C)For short-range,repetitive decisions
D)When making major,costly decisions,such as facilities location

Accepted Answer

Qualitative methods are best used for in-depth understanding of complex phenomena, situations or human experiences. However, they may not be appropriate for short-range, repetitive decisions that require quick and objective results. For major, costly decisions such as facilities location, quantitative methods may be more appropriate as they provide more accurate and reliable data for decision-making. Options A and B are not necessarily reasons to avoid qualitative methods as they can be used to gather new data or different perspectives when historical data are unreliable or unavailable.

Question 3

A small company that manufactures rubber boots is selecting a method to forecast demand for the next 10 years.The company recently expanded its facilities,doubling its capacity.Which of the following forecasting methods would be preferred?
A)Qualitative
B)Simple exponential smoothing
C)Econometric
D)Box-Jenkins

Accepted Answer

10 years is a long-range application, so qualitative methods will be most applicable.

Question 4

A method of forecasting that best describes the flows from one sector of the economy to another is called:
A)Regression
B)Econometric model
C)Input-output model
D)Simulation model

Accepted Answer

The input-output model is specifically designed to capture the flows of goods, services, and money between different sectors of the economy. This type of model is useful for forecasting how changes in one sector will impact other sectors, and for predicting the overall impact of certain policies or economic shocks. Regression, econometric, and simulation models may also be helpful in some contexts, but they are not specifically tailored to the task of modeling sector-to-sector flows.

Question 5

Given the following information for period 15,what will be the smoothed mean absolute deviation for period 16? Demand = 120 Forecast = 180 MAD₁₅ = 50 Alpha = 0.3 A)77 B)53 C)17 D)43

Accepted Answer

Using the formula for Simple exponential smoothing with MAD: MAD₁₆ = Alpha * ABS(Demand-Forecast) + (1-Alpha) * MAD₁₅ MAD₁₆ = 0.3 * ABS(120-180) + (1-0.3) * 50 = 53.

Question 6

Using exponential smoothing,if we want forecasts to be very responsive to recent demand,the value of alpha should be:
A)Large
B)Moderate
C)Small
D)The value of alpha does not matter.

Accepted Answer

The value of alpha determines the weight applied to the most recent demand observation when making forecasts. A large value of alpha will assign more weight to the most recent observation, making the forecast more responsive to changes in demand. Therefore, if we want forecasts to be very responsive to recent demand, we should choose a large value of alpha.

Question 7

If one time-series model is used for forecasting a low demand item and another time-series model is used for forecasting a high demand item,which measure of forecast accuracy provides a valid comparison of the errors from these two time-series?
A)CFE
B)MSE
C)MAD
D)MAPE

Accepted Answer

The purpose of MAPE is to normalize the error and allow comparison of different time series data.

Question 8

Which of the following is NOT a measure of forecast accuracy?
A)Mean square error
B)Cumulative sum of forecast error
C)Mean absolute deviation of forecast error
D)Cumulative absolute deviation of forecast error

Accepted Answer

A. B. and C are measures of forecast accuracy

Question 9

The Grand Bakery produces 60 special sourdough rolls every day.Any rolls that are not sold each day are given to the employees.They have collected sales data from the past week: $$\begin{array} { | c | c | } \hline \text { Day } & \text { Rolls sold } \ \hline 1 & 50 \ \hline 2 & 50 \ \hline 3 & 48 \ \hline 4 & 60 \ \hline 5 & 53 \ \hline 6 & 60 \ \hline \end{array}$$ What is the value of F₆ if they use a 3-day weighted moving average with W₁ = 0.6,W₂ = 0.2,and W₃ = 0.2? A)51.4 B)53.4 C)58.6 D)None of the above

Accepted Answer

To calculate the weighted moving average, we need to multiply the sales data by the weightage and sum them up. 
For Day 4:
WA = (0.6*48) + (0.2*50) + (0.2*50) = 28.8 + 10 + 10 = 48.8
For Day 5:
WA = (0.6*60) + (0.2*48) + (0.2*50) = 36 + 9.6 + 10 = 55.6
For Day 6:
WA = (0.6*53) + (0.2*60) + (0.2*48) = 31.8 + 12 + 9.6 = 53.4
So, the weighted moving average for Day 6 is 53.4.

Question 10

What is the exponentially smoothed forecast for week 2? (Use F₁ = 25 and alpha = 0.2) A)21 B)24 C)32 D)53

Accepted Answer

The exponentially smoothed forecast for week 2 can be calculated using the formula: FS1 = alpha * (Actual Sales Week 1) + (1-alpha) * (Forecast Week 1) where alpha = 0.2 F₁ = 25 (Forecast Week 1) If actual sales for Week 1 are not given, then we assume it to be equal to the forecast for Week 1. So, FS1 = 0.2 * 25 + 0.8 * 25 = 25 Therefore, the exponentially smoothed forecast for week 2 is 25, which is closest to option B (24).

Question 11

What is the exponentially smoothed forecast for week 6? (Use F₅ = 33 and alpha = 0.0) A)33 B)31.7 C)30 D)20

Accepted Answer

When alpha is 0, the exponentially smoothed forecast is simply equal to the most recent actual value, which in this case is 33.

Question 12

If a sales representative tells his or her manager,"I hope to sell 20% more than last year," this should be considered:
A)A forecast
B)A performance measure
C)A goal
D)A production plan

Accepted Answer

The statement "I hope to sell 20% more than last year" represents a specific target or objective that the sales representative hopes to achieve. Therefore, it can be considered a goal. It is not a forecast, as it does not involve predicting future sales based on past trends or data. It is also not a performance measure or a production plan, which refer to metrics used to evaluate past or current performance, or plans for how to achieve specific production targets, respectively.

Question 13

Which phrase most closely describes the Delphi forecasting technique?
A)Consumer survey
B)Individual opinions
C)Rounds of anonymous data collection
D)Test markets

Accepted Answer

The Delphi forecasting technique involves collecting data from multiple experts or participants anonymously over multiple rounds, with the goal of reaching a consensus forecast. It is not just a consumer survey or individual opinions, nor is it focused on test markets.

Question 14

Using a three-week moving average,what is your forecast for week 6?
A)30
B)35
C)32.5
D)25

Accepted Answer

The answer of Using a three-week moving average,what is your...

Question 15

Using the data from question 11,calculate the forecast for period 7 using a four-period moving average:
A)60
B)43.25
C)57.75
D)55.25

Accepted Answer

The answer of Using the data from question 11,calculate the...

Question 16

A qualitative forecast would most likely be used for:
A)Aggregate planning
B)Scheduling
C)Process design
D)Inventory management

Accepted Answer

The answer of A qualitative forecast would most likely be...

Question 17

A regression model is an example of which type of forecasting method?
A)Causal
B)Historical analogy
C)Qualitative
D)Life-cycle analogy

Accepted Answer

A regression model is a type of causal forecasting method as it attempts to establish a cause-and-effect relationship between the independent and dependent variables.

Question 18

The difference between actual demand and the forecast is:
A)Forecast error
B)Mean absolute percentage error
C)Absolute deviation of forecast error
D)Mean absolute deviation of forecast error

Accepted Answer

The difference between actual demand and the forecast is known as the forecast error. Therefore, option A is the correct choice. Mean absolute percentage error (B) and mean absolute deviation of forecast error (D) are metrics used to determine the accuracy of a forecast and are not the correct answer to this question. Option C, absolute deviation of forecast error, is not a defined metric in forecasting.

Question 19

Forecast error is used for all of the following EXCEPT:
A)To monitor erratic demand observations or outliers
B)To determine when the forecasting method is no longer tracking actual demand and needs to be reset
C)To determine the capacity cushion
D)To determine parameter values that provide the most accurate forecasts

Accepted Answer

Forecast error is not used to determine the capacity cushion. It is primarily used to monitor demand observations, evaluate the accuracy of forecasting methods, and identify when parameters need to be adjusted to improve the accuracy of forecasts.

Question 20

The forecast was 70 units for the current period while actual demand was 76.The forecast for the next period is 75.8.What is alpha if a simple exponential smoothing forecast method is being used?
A)0.004
B)0.967
C)0.040
D)0.097

Accepted Answer

Using the formula for simple exponential smoothing, we can calculate alpha as follows: 
Actual demand for current period = 76 
Forecast for current period = 70 
Forecast for next period = 75.8

76 = α(70) + (1-α)(70 + ε) 
76 = 70α + 70 - αε 
6 = α(ε) 
ε = 6/α

75.8 = α(76) + (1-α)(70 + ε) 
75.8 = 76α + 70 - αε 
5.8 = α(ε) 
5.8 = 6

Therefore, α = 0.967 (nearest three decimal places), which is the answer choice B.

Quiz 11: Forecasting

Which of the following statements is/are true about time-series forecasting?

When should qualitative methods NOT be used?

A small company that manufactures rubber boots is selecting a method to forecast demand for the next 10 years.The company recently expanded its facilities,doubling its capacity.Which of the following forecasting methods would be preferred?

A method of forecasting that best describes the flows from one sector of the economy to another is called:

Given the following information for period 15,what will be the smoothed mean absolute deviation for period 16? Demand = 120 Forecast = 180 MAD15 = 50 Alpha = 0.3

Using exponential smoothing,if we want forecasts to be very responsive to recent demand,the value of alpha should be:

If one time-series model is used for forecasting a low demand item and another time-series model is used for forecasting a high demand item,which measure of forecast accuracy provides a valid comparison of the errors from these two time-series?

Which of the following is NOT a measure of forecast accuracy?

What is the exponentially smoothed forecast for week 2? (Use F1 = 25 and alpha = 0.2)

What is the exponentially smoothed forecast for week 6? (Use F5 = 33 and alpha = 0.0)

If a sales representative tells his or her manager,"I hope to sell 20% more than last year," this should be considered:

Which phrase most closely describes the Delphi forecasting technique?

Using a three-week moving average,what is your forecast for week 6?

Using the data from question 11,calculate the forecast for period 7 using a four-period moving average:

A qualitative forecast would most likely be used for:

A regression model is an example of which type of forecasting method?

The difference between actual demand and the forecast is:

Forecast error is used for all of the following EXCEPT:

The forecast was 70 units for the current period while actual demand was 76.The forecast for the next period is 75.8.What is alpha if a simple exponential smoothing forecast method is being used?

Given the following information for period 15,what will be the smoothed mean absolute deviation for period 16? Demand = 120 Forecast = 180 MAD₁₅ = 50 Alpha = 0.3

What is the exponentially smoothed forecast for week 2? (Use F₁ = 25 and alpha = 0.2)

What is the exponentially smoothed forecast for week 6? (Use F₅ = 33 and alpha = 0.0)