Question 1

A seasonal index is a statistic that is computed from time-series data to indicate the effect of the seasonality in the time-series data.

Accepted Answer

A seasonal index measures how a particular season influences the activity being measured, compared to the average level of that activity. It is indeed computed from time-series data to quantify and adjust for seasonal effects.

Question 2

In comparing two or more forecasting models, the MAD value is useful in determining how successful the models were in fitting historical data.

Accepted Answer

MAD, or Mean Absolute Deviation, measures the average magnitude of errors between the forecasts and the actual values, thus indicating the accuracy of the forecasting models in fitting historical data.

Question 3

Renton Industries makes replacement parts for the automobile industry. As part of the company's capacity planning, it needs a long-range total demand forecast. The following information was generated based on 10 years of historical data on total number of parts sold each year.  Based on this information, we can conclude that sales on average have been growing by more than 48 thousand annually.

Accepted Answer

The answer of Renton Industries makes replacement parts for the...

Question 4

The Baker's Candy Company has been in business for three years. The quarterly sales data for the company are shown as follows:  Based on these data, the seasonal index for quarters 3, 7, and 11 is approximately 1.61

Accepted Answer

The answer of The Baker's Candy Company has been in...

Question 5

Gibson, Inc. is a holding company that owns several businesses. One such business is a truck sales company. To help in managing this operation, managers at Gibson have collected sales data for the past 20 years showing the number of trucks sold each year. They have then developed the linear trend forecasting model shown as follows:  Based on this information, it appears that the time series has a strong positive linear trend component.

Accepted Answer

The answer of Gibson, Inc. is a holding company that...

Question 6

In using simple linear regression to find the linear trend in an annual time series from 2000 to 2015, the values 2000, 2001, etc. are used as the values of the independent variable t when the regression is conducted.

Accepted Answer

The answer of In using simple linear regression to find...

Question 7

The Baker's Candy Company has been in business for three years. The quarterly sales data for the company are shown as follows:  As a first step in computing a seasonal index, the four-period moving average corresponding to the mid- point between periods 2 and 3 is 3,350.

Accepted Answer

The answer of The Baker's Candy Company has been in...

Question 8

The reason for using split samples in developing a forecasting model is to eliminate the potential for bias in the resulting model.

Accepted Answer

Split samples are used to validate the model's performance and ensure it generalizes well to new data, not specifically to eliminate bias.

Question 9

One of the disadvantages of a regression-based linear trend forecasting model is that the forecast errors are computed for time periods that were used in developing the forecasting model and thus do not truly measure the forecasting ability of the model.

Accepted Answer

The forecast errors computed during the development of a regression-based linear trend forecasting model are based on the same data used to create the model, which means they do not necessarily reflect the model's ability to predict future, unseen data points.

Question 10

It is possible to use linear regression analysis to develop a forecasting model for nonlinear data if we can effectively transform the data.

Accepted Answer

Linear regression can be applied to nonlinear data by transforming the data into a linear form through mathematical functions, making it possible to develop a forecasting model.

Question 11

The Baker's Candy Company has been in business for three years. The quarterly sales data for the company are shown as follows:  Based on this information, the data reflect both a linear trend and seasonal components.

Accepted Answer

The answer of The Baker's Candy Company has been in...

Question 12

Renton Industries makes replacement parts for the automobile industry. As part of the company's capacity planning, it needs a long-range total demand forecast. The following information was generated based on 10 years of historical data on total number of parts sold each year.  Based on this information, the percent of variation in the number of parts sold that is explained by the linear trend model is approximately 90.9.

Accepted Answer

The answer of Renton Industries makes replacement parts for the...

Question 13

Forecast bias measures the average amount of error per forecast, so a positive value means that forecasts tended to be too low.

Accepted Answer

Forecast bias is an indicator of whether a forecast tends to be higher or lower than the actual values. A positive forecast bias indicates that the forecasts were consistently lower than the actual outcomes, meaning the forecasts underestimated the actual values.

Question 14

In a time series with monthly sales data, a spring quarter seasonal index of 1.21 can be interpreted to mean that sales tend to be 21 percent higher in the spring quarter when compared to the other quarters.

Accepted Answer

A seasonal index of 1.21 indicates that sales in the spring quarter are 21% higher than the average sales of all quarters, reflecting a seasonal effect.

Question 15

A scatter plot of time series data with time on the vertical axis is an effective means of assessing whether the series is linear or nonlinear.

Accepted Answer

A scatter plot with time on the horizontal axis and the variable of interest on the vertical axis is the conventional and effective way to assess linearity or nonlinearity in time series data.

Question 16

You are given the following linear trend model: Ft = 345.60 - 200.5(t). This model implies that in year 1, the dependent variable had a value of 145.1.

Accepted Answer

The model implies that in year 1 (t=1), the dependent variable would be Ft = 345.60 - 200.5(1) = 145.1, which is correct. However, the statement is false because it incorrectly suggests that the model implies this value without calculation.

Question 17

Gibson, Inc. is a holding company that owns several businesses. One such business is a truck sales company. To help in managing this operation, managers at Gibson have collected sales data for the past 20 years showing the number of trucks sold each year. They have then developed the linear trend forecasting model shown as follows:  Based on this information, the fitted value for year 1 is about 99.

Accepted Answer

The answer of Gibson, Inc. is a holding company that...

Question 18

In measuring forecast errors, the MAD and the square root of the MSE will provide similar (but not identical) values, in that both provide a measure of the "typical" amount of error in forecasts.

Accepted Answer

Both MAD (Mean Absolute Deviation) and the square root of MSE (Mean Squared Error) are measures of forecast accuracy that provide an average magnitude of errors, with MAD using absolute errors and the square root of MSE penalizing larger errors more due to squaring.

Question 19

Renton Industries makes replacement parts for the automobile industry. As part of the company's capacity planning, it needs a long-range total demand forecast. The following information was generated based on 10 years of historical data on total number of parts sold each year.  Based on this information we can conclude that the linear trend model explains a significant proportion of the variation in the number of parts sold, because the p-value is much smaller than any reasonable α that we might use.

Accepted Answer

The answer of Renton Industries makes replacement parts for the...

Question 20

From an annual time series of a company's employee income, the linear trend model Ft = 165 - 54(t) has been developed. This means that on average income has been increasing by 165 per year.

Accepted Answer

The coefficient -54(t) indicates that on average, income has been decreasing by 54 per year, not increasing.

Quiz 16: Analyzing and Forecasting Time-Series Data

A seasonal index is a statistic that is computed from time-series data to indicate the effect of the seasonality in the time-series data.

In comparing two or more forecasting models, the MAD value is useful in determining how successful the models were in fitting historical data.

The Baker's Candy Company has been in business for three years. The quarterly sales data for the company are shown as follows: Based on these data, the seasonal index for quarters 3, 7, and 11 is approximately 1.61

In using simple linear regression to find the linear trend in an annual time series from 2000 to 2015, the values 2000, 2001, etc. are used as the values of the independent variable t when the regression is conducted.

The Baker's Candy Company has been in business for three years. The quarterly sales data for the company are shown as follows: As a first step in computing a seasonal index, the four-period moving average corresponding to the mid- point between periods 2 and 3 is 3,350.

The reason for using split samples in developing a forecasting model is to eliminate the potential for bias in the resulting model.

One of the disadvantages of a regression-based linear trend forecasting model is that the forecast errors are computed for time periods that were used in developing the forecasting model and thus do not truly measure the forecasting ability of the model.

It is possible to use linear regression analysis to develop a forecasting model for nonlinear data if we can effectively transform the data.

The Baker's Candy Company has been in business for three years. The quarterly sales data for the company are shown as follows: Based on this information, the data reflect both a linear trend and seasonal components.

Forecast bias measures the average amount of error per forecast, so a positive value means that forecasts tended to be too low.

In a time series with monthly sales data, a spring quarter seasonal index of 1.21 can be interpreted to mean that sales tend to be 21 percent higher in the spring quarter when compared to the other quarters.

A scatter plot of time series data with time on the vertical axis is an effective means of assessing whether the series is linear or nonlinear.

You are given the following linear trend model: Ft = 345.60 - 200.5(t). This model implies that in year 1, the dependent variable had a value of 145.1.

In measuring forecast errors, the MAD and the square root of the MSE will provide similar (but not identical) values, in that both provide a measure of the "typical" amount of error in forecasts.

From an annual time series of a company's employee income, the linear trend model Ft = 165 - 54(t) has been developed. This means that on average income has been increasing by 165 per year.