Question 1

Which of the following methods tells whether the forecast tends to be too high or too low?
A) MAD
B) MSE
C) MAPE
D) decomposition
E) bias

Accepted Answer

Bias is the measure of the tendency of the forecast to overestimate or underestimate the actual values. A positive bias indicates that the forecast tends to be too low, whereas a negative bias indicates that the forecast tends to be too high. Therefore, bias is the method that tells whether the forecast tends to be too high or too low.

Question 2

The computer monitoring of tracking signals and self-adjustment is referred to as
A) exponential smoothing.
B) adaptive smoothing.
C) trend projections.
D) trend smoothing.
E) running sum of forecast errors (RFSE).

Accepted Answer

The process described in the question is an example of adaptive smoothing, where the computer continuously monitors and adjusts forecasts based on tracking signals. The other options listed (exponential smoothing, trend projections, trend smoothing, and RFSE) do not necessarily involve computer monitoring or self-adjustment.

Question 3

Enrollment in a particular class for the last four semesters has been 120, 126, 110, and 130 (listed from oldest to most recent). Develop a forecast of enrollment next semester using exponential smoothing with an alpha = 0.2. Assume that an initial forecast for the first semester was 120 (so the forecast and the actual were the same).
A) 118.96
B) 121.17
C) 130
D) 120
E) None of the above

Accepted Answer

Using exponential smoothing with alpha = 0.2:
Forecast for semester 1 = 120
Actual enrollment for semester 1 = 120
Forecast for semester 2 = (0.2 x 120) + (0.8 x 120) = 120 (the same as the actual enrollment)
Actual enrollment for semester 2 = 126

Using the forecast for semester 2 as the starting point, we can calculate the forecast for semester 3 as:
Forecast for semester 3 = (0.2 x 126) + (0.8 x 120) = 121.2

Continuing this pattern, the forecast for semester 4 is:
Forecast for semester 4 = (0.2 x 130) + (0.8 x 121.2) = 121.96 or 122 (rounded to nearest whole number)

Therefore, the best choice is B, 121.17.

Question 4

Demand for soccer balls at a new sporting goods store is forecasted using the following regression equation: Y = 98 + 2.2X where X is the number of months that the store has been in existence. Let April be represented by X = 4. April is assumed to have a seasonality index of 1.15. What is the forecast for soccer ball demand for the month of April (rounded to the nearest integer)?
A) 123
B) 107
C) 100
D) 115
E) None of the above

Accepted Answer

The answer of Demand for soccer balls at a new...

Question 5

As one increases the number of periods used in the calculation of a moving average,
A) greater emphasis is placed on more recent data.
B) less emphasis is placed on more recent data.
C) the emphasis placed on more recent data remains the same.
D) it requires a computer to automate the calculations.
E) one is usually looking for a long-term prediction.

Accepted Answer

The answer of As one increases the number of periods...

Question 6

Which of the following is not a characteristic of trend projections?
A) The variable being predicted is the Y variable.
B) Time is the X variable.
C) It is useful for predicting the value of one variable based on time trend.
D) A negative intercept term always implies that the dependent variable is decreasing over time.
E) They are often developed using linear regression.

Accepted Answer

A negative intercept term does not always imply that the dependent variable is decreasing over time. It may simply indicate that the starting point for the trend projection is below zero or the baseline.

Question 7

Daily demand for newspapers for the last 10 days has been as follows: 12, 13, 16, 15, 12, 18, 14, 12, 13, 15 (listed from oldest to most recent). Forecast sales for the next day using a three-day weighted moving average where the weights are 3, 1, and 1 (the highest weight is for the most recent number).
A) 12.8
B) 13.0
C) 70.0
D) 14.0
E) None of the above

Accepted Answer

The answer of Daily demand for newspapers for the last...

Question 8

Which of the following methods produces a particularly stiff penalty in periods with large forecast errors?
A) MAD
B) MSE
C) MAPE
D) decomposition
E) bias

Accepted Answer

The answer of Which of the following methods produces a...

Question 9

Daily demand for newspapers for the last 10 days has been as follows: 12, 13, 16, 15, 12, 18, 14, 12, 13, 15 (listed from oldest to most recent). Forecast sales for the next day using a two-day weighted moving average where the weights are 3 and 1 are
A) 14.5.
B) 13.5.
C) 14.
D) 12.25.
E) 12.75.

Accepted Answer

To calculate the two-day weighted moving average, use the formula: (Weight1 * Demand1 + Weight2 * Demand2) / (Weight1 + Weight2). For the last two days, the demand was 13 and 15. Using weights 3 and 1: (3*15 + 1*13) / (3+1) = (45 + 13) / 4 = 58 / 4 = 14.5.

Question 10

Sales for boxes of Girl Scout cookies over a 4-month period were forecasted as follows: 100, 120, 115, and 123. The actual results over the 4-month period were as follows: 110, 114, 119, 115. What was the MSE of the 4-month forecast?
A) 0
B) 5
C) 7
D) 108
E) None of the above

Accepted Answer

The answer of Sales for boxes of Girl Scout cookies...

Question 11

Assume that you have tried three different forecasting models. For the first, the MAD = 2.5, for the second, the MSE = 10.5, and for the third, the MAPE = 2.7. We can then say:
A) the third method is the best.
B) the second method is the best.
C) methods one and three are preferable to method two.
D) method two is least preferred.
E) None of the above

Accepted Answer

The answer of Assume that you have tried three different...

Question 12

Daily demand for newspapers for the last 10 days has been as follows: 12, 13, 16, 15, 12, 18, 14, 12, 13, 15 (listed from oldest to most recent). Forecast sales for the next day using a two-day moving average.
A) 14
B) 13
C) 15
D) 28
E) 12.5

Accepted Answer

The answer of Daily demand for newspapers for the last...

Question 13

A time-series forecasting model in which the forecast for the next period is the actual value for the current period is the
A) Delphi model.
B) Holt's model.
C) naïve model.
D) exponential smoothing model.
E) weighted moving average.

Accepted Answer

The naïve model is a simple time-series forecasting model that assumes the best predictor of the future value is the current value. Therefore, the forecast for the next period is simply the actual value for the current period. This model is useful as a baseline for evaluating the performance of more advanced forecasting techniques. However, it may not be suitable for datasets with significant trends, seasonality, or other patterns that require more sophisticated modeling approaches.

Question 14

Which of the following is not considered to be one of the components of a time series?
A) trend
B) seasonality
C) variance
D) cycles
E) random variations

Accepted Answer

Variance is not considered to be one of the components of a time series. The four main components of a time series are trend, seasonality, cycles, and random variations.

Question 15

Sales for boxes of Girl Scout cookies over a 4-month period were forecasted as follows: 100, 120, 115, and 123. The actual results over the 4-month period were as follows: 110, 114, 119, 115. What was the MAD of the 4-month forecast?
A) 0
B) 5
C) 7
D) 108
E) None of the above

Accepted Answer

To calculate the MAD, we need to find the absolute deviations for each month and then find their average.

Absolute deviations: 
Month 1: |100-110| = 10 
Month 2: |120-114| = 6 
Month 3: |115-119| = 4 
Month 4: |123-115| = 8

Average of absolute deviations: (10+6+4+8)/4 = 7

Therefore, the MAD of the 4-month forecast is 7. Option (C) is the correct choice.

Question 16

Which of the following methods gives an indication of the percentage of forecast error?
A) MAD
B) MSE
C) MAPE
D) decomposition
E) bias

Accepted Answer

MAPE (Mean Absolute Percentage Error) gives an indication of the percentage of forecast error by calculating the average percentage difference between actual and forecasted values. MAD (Mean Absolute Deviation) and MSE (Mean Squared Error) give an indication of the magnitude of the forecast error but not as a percentage. Decomposition breaks down the time series into trend, seasonal, and residual components and does not directly provide an indication of the forecast error percentage. Bias is a measure of the direction and consistency of forecast errors but does not indicate the percentage of forecast error.

Question 17

When both trend and seasonal components are present in time series, which of the following is most appropriate?
A) the use of centered moving averages
B) the use of moving averages
C) the use of simple exponential smoothing
D) the use of weighted moving averages
E) the use of double smoothing

Accepted Answer

Centered moving averages are used to remove both trend and seasonal components from a time series, making it suitable for analyzing data with both characteristics.

Question 18

Enrollment in a particular class for the last four semesters has been 122, 128, 100, and 155 (listed from oldest to most recent). The best forecast of enrollment next semester, based on a three-semester moving average, would be
A) 116.7.
B) 126.3.
C) 168.3.
D) 135.0.
E) 127.7.

Accepted Answer

The answer of Enrollment in a particular class for the...

Question 19

In picking the smoothing constant for an exponential smoothing model, we should look for a value that
A) produces a nice-looking curve.
B) equals the utility level that matches with our degree of risk aversion.
C) produces values which compare well with actual values based on a standard measure of error.
D) causes the least computational effort.
E) None of the above

Accepted Answer

The best choice for the smoothing constant in an exponential smoothing model is the one that produces values that compare well with actual values based on a standard measure of error. This ensures that the model is accurately predicting future values and is reliable for decision-making purposes. The other options listed are not as relevant to the accuracy of the model.

Question 20

In the exponential smoothing with trend adjustment forecasting method, is the
A) slope of the trend line.
B) new forecast.
C) Y-axis intercept.
D) independent variable.
E) trend smoothing constant.

Accepted Answer

β is the trend smoothing constant in the exponential smoothing with trend adjustment forecasting method. It controls the rate at which the trend adjusts to changes in the data.

Quiz 5: Forecasting

Which of the following methods tells whether the forecast tends to be too high or too low?

The computer monitoring of tracking signals and self-adjustment is referred to as

As one increases the number of periods used in the calculation of a moving average,

Which of the following is not a characteristic of trend projections?

Which of the following methods produces a particularly stiff penalty in periods with large forecast errors?

Daily demand for newspapers for the last 10 days has been as follows: 12, 13, 16, 15, 12, 18, 14, 12, 13, 15 (listed from oldest to most recent) . Forecast sales for the next day using a two-day weighted moving average where the weights are 3 and 1 are

Sales for boxes of Girl Scout cookies over a 4-month period were forecasted as follows: 100, 120, 115, and 123. The actual results over the 4-month period were as follows: 110, 114, 119, 115. What was the MSE of the 4-month forecast?

Assume that you have tried three different forecasting models. For the first, the MAD = 2.5, for the second, the MSE = 10.5, and for the third, the MAPE = 2.7. We can then say:

Daily demand for newspapers for the last 10 days has been as follows: 12, 13, 16, 15, 12, 18, 14, 12, 13, 15 (listed from oldest to most recent) . Forecast sales for the next day using a two-day moving average.

A time-series forecasting model in which the forecast for the next period is the actual value for the current period is the

Which of the following is not considered to be one of the components of a time series?

Sales for boxes of Girl Scout cookies over a 4-month period were forecasted as follows: 100, 120, 115, and 123. The actual results over the 4-month period were as follows: 110, 114, 119, 115. What was the MAD of the 4-month forecast?

Which of the following methods gives an indication of the percentage of forecast error?

When both trend and seasonal components are present in time series, which of the following is most appropriate?

Enrollment in a particular class for the last four semesters has been 122, 128, 100, and 155 (listed from oldest to most recent) . The best forecast of enrollment next semester, based on a three-semester moving average, would be

In picking the smoothing constant for an exponential smoothing model, we should look for a value that

In the exponential smoothing with trend adjustment forecasting method, is the