Question 1

In a recent meeting, the sales manager for a drug company stated that she needed to have a forecast prepared for each week for the next six weeks. The week in this case is the:
A) forecasting horizon.
B) forecasting period.
C) planning time.
D) forecasting interval.

Accepted Answer

The forecasting period refers to the length of time into the future for which forecasts are prepared, which in this case is each week.

Question 2

If you suspect that your trend forecasting model may have autocorrelated forecast errors, which the following should you compute?
A) The MAD
B) The standard error of the estimate
C) The Durbin-Watson test statistic
D) The correlation coefficient

Accepted Answer

The Durbin-Watson test statistic is specifically designed to detect the presence of autocorrelation in the residuals from a regression analysis, making it the appropriate choice for investigating autocorrelated forecast errors.

Question 3

Which of the following statements about the Durbin-Watson d statistic is true?
A) It can assume any value between 0 and 4.
B) It may assume any value between -4 and + 4.
C) It may assume any positive value.
D) It has a maximum value of 2.

Accepted Answer

The Durbin-Watson d statistic is used to detect the presence of autocorrelation in the residuals from a regression analysis. It ranges from 0 to 4, where a value of 2 indicates no autocorrelation, values approaching 0 indicate positive autocorrelation, and values approaching 4 indicate negative autocorrelation.

Question 4

Which of the following is true about index numbers? Index numbers are:
A) used to measure the trend component.
B) used to measure the seasonal component.
C) used to measure the cyclical component.
D) used to make a relative comparison of different time periods.

Accepted Answer

Index numbers are primarily used for making relative comparisons between different time periods, allowing for the assessment of trends, economic changes, price movements, or productivity changes over time. They are not specifically designed to measure the trend, seasonal, or cyclical components individually, but rather to provide a general comparison across periods.

Question 5

The following output is provided for a linear trend regression-based forecasting model based on 12 months of data:  Suppose that the actual sales for months 13-15 are: 720, 680, 800. Given this, which of the following is the forecast bias value for months 13-15?
A) Approximately 77.7
B) Approximately 233.2
C) About -56.8
D) Just under 80

Accepted Answer

The answer of The following output is provided for a...

Question 6

Which of the following statistical measures is used to help decision makers assess the potential for their model to provide usable forecasts?
A) The mean absolute deviation
B) The mean square error
C) Both A and B
D) Neither A nor B

Accepted Answer

Both the mean absolute deviation and the mean square error are statistical measures used to assess the accuracy of forecasting models, helping decision makers evaluate the potential usability of their forecasts.

Question 7

Which of the following is true regarding the MSE and MAD in forecasting?
A) The MAD will tend to be a larger value than the MSE.
B) The MSE is much more useful than the MAD.
C) The square root of the MSE provides a value that will be similar to the MAD.
D) The MAD will be equal to the MSE.

Accepted Answer

The Mean Squared Error (MSE) is the average of the squares of the errors, while the Mean Absolute Deviation (MAD) is the average of the absolute values of the errors. Taking the square root of the MSE (which gives the Root Mean Squared Error, RMSE) makes it more directly comparable to the MAD, as both then represent average error magnitudes in the same units as the original data.

Question 8

The Cresswell Company updates its annual sales forecast every month as new sales data becomes available. The one-month update is called:
A) the planning horizon.
B) the forecast period.
C) the forecast interval.
D) the forecasting horizon.

Accepted Answer

The forecast interval refers to the time period between each forecast update, which in this case is one month as the company updates its annual sales forecast monthly.

Question 9

Which of the following is true about forecast bias?
A) It is the mean absolute deviation.
B) It is equal to the square root of the MSE.
C) When it is negative it means that the forecasts tended to be high.
D) When it is positive it means that the forecasts tended to be high.

Accepted Answer

When forecast bias is negative, it means that the forecasts tended to be high.

Question 10

A time-series plot that exhibits a general increase in value from the early periods to the latest time periods:
A) most likely is exhibiting a cyclical component.
B) has a trend component present in the data.
C) will probably start to decline in a few periods.
D) has a seasonal component present in the data

Accepted Answer

A time-series plot that shows a general increase in value from the early periods to the latest time periods is indicative of a trend component, which reflects long-term progression in the data.

Question 11

A company has recorded the 12 months of sales data for the past year. It wishes to use the regression approach to develop a trend-based approach for forecasting future months. The following data are provided:  Based on this information, which of the following is forecast for month 15?
A) Approximately 692
B) About 596
C) Just over 825
D) None of the above

Accepted Answer

The answer of A company has recorded the 12 months...

Question 12

A company has developed a linear trend model to forecast monthly sales. The following data show the actual sales and the "fitted" sales for months 1-12.  Based on these data, what is the value for the mean absolute deviation for months 1-12?
A) Approximately 975
B) About 81
C) Nearly 150
D) None of the above

Accepted Answer

The answer of A company has developed a linear trend...

Question 13

If a company has 12 years of annual sales data and is in need of a three-year forecast, which of the following forecasting techniques might be useful?
A) Forecast generalization
B) Seasonality processing
C) Regression-based trend forecasting
D) Random component analysis

Accepted Answer

Regression-based trend forecasting is useful for making forecasts based on historical data, such as 12 years of annual sales data, by identifying the relationship between time and sales to predict future trends.

Question 14

Which of the following time-series components is almost always present in sales data for electronics companies?
A) Random
B) Trend
C) Seasonal
D) All of the above

Accepted Answer

The answer of Which of the following time-series components is...

Question 15

A company has recorded annual sales for the past 14 years and found the following linear trend model: 
A) on average sales are increasing by of 5.23 per year.
B) on average sales are increasing by of 144.6 per year.
C) there is a seasonal component in the data.
D) sales in year 1 were 5.23.

Accepted Answer

The answer of A company has recorded annual sales for...

Question 16

Assume that the year 2000 is used as the index base period and that sales were 12 million in the year 2000. If sales were 18 million in the year 2006, the simple index number for the year 2006 is:
A) 1.5
B) 6 million
C) 150
D) 0.666

Accepted Answer

The simple index number is calculated by dividing the sales in 2006 by the sales in the base year (2000) and then multiplying by 100. So, (18 million / 12 million) * 100 = 150.

Question 17

A company has recorded 12 months of sales data for the past year and has found the linear trend equation is  Based on this information, which of the following is the forecast for period 13?
A) 3718
B) 842.4
C) 350.8
D) 1129.7

Accepted Answer

The answer of A company has recorded 12 months of...

Question 18

Which of the following time-series components can be identified when a company has 12 weeks of data beginning January and extending through March?
A) Seasonal component
B) Random component
C) Trend component
D) Both B and C

Accepted Answer

With 12 weeks of data, it's possible to identify both random variations and potential trends, but it's generally too short a period to conclusively identify seasonal components, which typically require at least a year of data to discern patterns related to seasons or specific times of the year.

Question 19

A company has a monthly time series that regularly shows sales being higher in the summer months. This is an example of which component?
A) Trend
B) Seasonal
C) Cyclical
D) Random

Accepted Answer

Seasonal components are patterns that repeat over a specific period, such as months, quarters, or years. In this case, sales being higher in the summer months is a pattern that repeats every year, making it a seasonal component.

Question 20

A company has developed a linear trend model to forecast monthly sales. The following data show the actual sales and the "fitted" sales for months 1-12.  Based on these data, what is the mean square error for the linear trend model?
A) Approximately 7,968
B) About 99,615
C) Nearly 18,000
D) None of the above

Accepted Answer

The answer of A company has developed a linear trend...

Quiz 16: Analyzing and Forecasting Time-Series Data

In a recent meeting, the sales manager for a drug company stated that she needed to have a forecast prepared for each week for the next six weeks. The week in this case is the:

If you suspect that your trend forecasting model may have autocorrelated forecast errors, which the following should you compute?

Which of the following statements about the Durbin-Watson d statistic is true?

Which of the following is true about index numbers? Index numbers are:

The following output is provided for a linear trend regression-based forecasting model based on 12 months of data: Suppose that the actual sales for months 13-15 are: 720, 680, 800. Given this, which of the following is the forecast bias value for months 13-15?

Which of the following statistical measures is used to help decision makers assess the potential for their model to provide usable forecasts?

Which of the following is true regarding the MSE and MAD in forecasting?

The Cresswell Company updates its annual sales forecast every month as new sales data becomes available. The one-month update is called:

Which of the following is true about forecast bias?

A time-series plot that exhibits a general increase in value from the early periods to the latest time periods:

A company has recorded the 12 months of sales data for the past year. It wishes to use the regression approach to develop a trend-based approach for forecasting future months. The following data are provided: Based on this information, which of the following is forecast for month 15?

A company has developed a linear trend model to forecast monthly sales. The following data show the actual sales and the "fitted" sales for months 1-12. Based on these data, what is the value for the mean absolute deviation for months 1-12?

If a company has 12 years of annual sales data and is in need of a three-year forecast, which of the following forecasting techniques might be useful?

Which of the following time-series components is almost always present in sales data for electronics companies?

A company has recorded annual sales for the past 14 years and found the following linear trend model:

Assume that the year 2000 is used as the index base period and that sales were 12 million in the year 2000. If sales were 18 million in the year 2006, the simple index number for the year 2006 is:

A company has recorded 12 months of sales data for the past year and has found the linear trend equation is Based on this information, which of the following is the forecast for period 13?

Which of the following time-series components can be identified when a company has 12 weeks of data beginning January and extending through March?

A company has a monthly time series that regularly shows sales being higher in the summer months. This is an example of which component?

A company has developed a linear trend model to forecast monthly sales. The following data show the actual sales and the "fitted" sales for months 1-12. Based on these data, what is the mean square error for the linear trend model?