Question 1

Double exponential smoothing is used instead of single exponential smoothing when extra smooth forecasts are desired.

Accepted Answer

Double exponential smoothing is used to account for trends in the data, not just to achieve extra smooth forecasts. Single exponential smoothing does not account for trends.

Question 2

Because simple exponential smoothing models require a starting point for the first period forecast that will be arbitrary,it is important to have as much data as possible to dampen out the effect of the starting point.

Accepted Answer

Simple exponential smoothing models are influenced by the starting point of the first period forecast. Having more data helps to reduce the impact of this arbitrary starting point on the accuracy of the forecast.

Question 3

The Morgan Company is interested in developing a forecast for next month's sales.It has collected sales data for the past 12 months.  Assuming that the company plans to use double exponential smoothing with starting values for the smoothed constant process value and smoothed trend value of 98.97 and 13.16 respectively,the MAD value for periods 2-12 is greater when alpha = 0.20 and beta = 0.20 than when alpha = 0.10 and beta = 0.10.

Accepted Answer

The answer of The Morgan Company is interested in developing...

Question 4

The process of selecting the forecasting technique to use in a particular application is called:
A)model diagnosis.
B)model specification.
C)validity checking.
D)model fitting.

Accepted Answer

The process of selecting the forecasting technique to use in a particular application is called model specification. This involves considering factors such as the type of data available, the time period to be forecasted, and the underlying causal factors influencing the variable being forecasted. Model specification is important in ensuring that the chosen technique is appropriate for the specific situation and can produce accurate and reliable forecasts.

Question 5

If you suspect that your time-series data has a strong downward trend,you should set the beta smoothing constant at value fairly close to negative 1.0.

Accepted Answer

The beta smoothing constant in time-series analysis, such as in exponential smoothing models, should be between 0 and 1. It does not take negative values. Adjusting it closer to 1 would increase responsiveness to trend changes, not set a direction of the trend.

Question 6

In establishing a single exponential smoothing forecasting model,a starting point for the forecast value for period 1 is required.One method for arriving at this starting point is to use the first data point as the forecast for that period.If we do that,then the first data point should be ignored when computing measures of forecast error.

Accepted Answer

When the first data point is used as the starting point for a single exponential smoothing forecast, it is not included when computing measures of forecast error. This is because there is no actual forecast involved for that period.

Question 7

In a recent meeting,the marketing manager for a large hardware company stated that he needed to have a forecast prepared for the next three months.The three-month period is called:
A)the forecasting horizon.
B)the forecasting period.
C)the planning time.
D)a business cycle.

Accepted Answer

The three-month period is the time frame for which the marketing manager needs a forecast. This time frame is referred to as the forecasting horizon, which is the period for which the forecast is made.

Question 8

In a single exponential smoothing model,one smoothing constant is used to weigh the historical data,and the model is of primary value when the data do not exhibit trend or seasonal components.

Accepted Answer

This statement is correct. A single exponential smoothing model uses one smoothing constant to weigh historical data, and the model is most accurate when the data does not have trend or seasonality.

Question 9

In a single exponential smoothing model,a large value for the smoothing constant will result in greater smoothing of the data than will a smoothing constant close to zero.

Accepted Answer

A large value for the smoothing constant (close to 1) gives more weight to the most recent observation, resulting in less smoothing. A smoothing constant close to zero results in greater smoothing because it gives more weight to past observations.

Question 10

The Morgan Company is interested in developing a forecast for next month's sales.It has collected sales data for the past 12 months.  After analyzing these data,if the company wishes to use exponential smoothing,it should employ a single smoothing model since there is evidence of a linear trend in the data.

Accepted Answer

If there is evidence of a linear trend in the data, a double smoothing model (Holt's linear method) would be more appropriate for forecasting. Exponential smoothing is better suited for data with no trend or a stable trend.

Question 11

If a smoothing model is applied with a smoothing constant exceeding 0.50,the forecasting bias will tend to be positive in most cases.

Accepted Answer

The answer of If a smoothing model is applied with...

Question 12

The owners of Hal's Cookie Company have collected sales data for the past 8 months.These data are shown as follows:  Using a smoothing constant of 0.4,the forecast value for period 3 is 112.

Accepted Answer

The answer of The owners of Hal's Cookie Company have...

Question 13

The Morgan Company is interested in developing a forecast for next month's sales.It has collected sales data for the past 12 months.  After analyzing these data,if the company wishes to use exponential smoothing with alpha = 0.20 and beta = 0.20,the starting values for the constant process and the trend process can be derived from a linear trend regression model by using the intercept and slope coefficient respectively.

Accepted Answer

Yes, the starting values for exponential smoothing with alpha and beta can be derived from a linear trend regression model by using the intercept and slope coefficient, respectively. This is because the linear trend regression model provides estimates for the level and trend components of the time series, which are the starting values for the constant process and trend process in exponential smoothing.

Question 14

The owners of Hal's Cookie Company have collected sales data for the past 8 months.These data are shown as follows:  Using a smoothing constant equal to 0.20 and starting forecast in period 1 of 100,the forecast value for period 9 is approximately 104.2.

Accepted Answer

The answer of The owners of Hal's Cookie Company have...

Question 15

If a time series contains substantial irregular movement,the smoothing constant for a single exponential smoothing model that is close to 1.0 will result in forecasts that are not as smoothed out as those that would occur if a smaller smoothing constant was used.

Accepted Answer

A larger smoothing constant will put more weight on recent observations and less weight on past observations, leading to less smoothing and a closer fit to the irregular movement in the time series. A smaller smoothing constant would put more weight on past observations and result in more smoothing.

Question 16

If a time-series plot indicates that the data do not appear to exhibit a trend,then a double exponential smoothing model would likely be the most appropriate to use rather than simple exponential smoothing model.

Accepted Answer

If the data do not exhibit a trend, a simple exponential smoothing model can still be appropriate for forecasting. A double exponential smoothing model, which includes trend smoothing, may introduce unnecessary complexity and overfitting to the data.

Question 17

In a double smoothing model,the second smoothing constant is introduced to account for the trend in the data if one exists.

Accepted Answer

This is true. Double smoothing, also known as Holt's linear exponential smoothing, includes a second smoothing constant (or coefficient) to estimate and account for trend in the data.

Question 18

Prior to conducting double exponential smoothing a simple linear regression is conducted and the trend equation is = 42 + 38.3t,so the smoothed constant process value should be C₀ = 38.3 and the smoothed trend value should be T₀ = 42.

Accepted Answer

The answer of Prior to conducting double exponential smoothing a...

Question 19

In a double smoothing model,large values for the two smoothing constants will result in greater smoothing of the time series.

Accepted Answer

In a double smoothing model, large values for the two smoothing constants actually result in less smoothing and more responsiveness to recent changes in the data.

Question 20

The owners of Hal's Cookie Company have collected sales data for the past 8 months.These data are shown as follows:  Using a starting forecast in period 1 of 100,the forecast bias over periods 2-8 is negative when a single exponential smoothing model is used with a smoothing constant of 0.20.

Accepted Answer

We cannot determine if the answer is true or false based on the given information. The fact that the forecast bias over periods 2-8 is negative does not necessarily mean that the single exponential smoothing model with a smoothing constant of 0.20 is the cause. Other factors could be influencing the sales data.

Quiz 16: Analyzing and Forecasting Time-Series Data

Double exponential smoothing is used instead of single exponential smoothing when extra smooth forecasts are desired.

Because simple exponential smoothing models require a starting point for the first period forecast that will be arbitrary,it is important to have as much data as possible to dampen out the effect of the starting point.

The process of selecting the forecasting technique to use in a particular application is called:

If you suspect that your time-series data has a strong downward trend,you should set the beta smoothing constant at value fairly close to negative 1.0.

In a recent meeting,the marketing manager for a large hardware company stated that he needed to have a forecast prepared for the next three months.The three-month period is called:

In a single exponential smoothing model,one smoothing constant is used to weigh the historical data,and the model is of primary value when the data do not exhibit trend or seasonal components.

In a single exponential smoothing model,a large value for the smoothing constant will result in greater smoothing of the data than will a smoothing constant close to zero.

If a smoothing model is applied with a smoothing constant exceeding 0.50,the forecasting bias will tend to be positive in most cases.

The owners of Hal's Cookie Company have collected sales data for the past 8 months.These data are shown as follows: Using a smoothing constant of 0.4,the forecast value for period 3 is 112.

The owners of Hal's Cookie Company have collected sales data for the past 8 months.These data are shown as follows: Using a smoothing constant equal to 0.20 and starting forecast in period 1 of 100,the forecast value for period 9 is approximately 104.2.

If a time series contains substantial irregular movement,the smoothing constant for a single exponential smoothing model that is close to 1.0 will result in forecasts that are not as smoothed out as those that would occur if a smaller smoothing constant was used.

If a time-series plot indicates that the data do not appear to exhibit a trend,then a double exponential smoothing model would likely be the most appropriate to use rather than simple exponential smoothing model.

In a double smoothing model,the second smoothing constant is introduced to account for the trend in the data if one exists.

Prior to conducting double exponential smoothing a simple linear regression is conducted and the trend equation is = 42 + 38.3t,so the smoothed constant process value should be C0 = 38.3 and the smoothed trend value should be T0 = 42.

In a double smoothing model,large values for the two smoothing constants will result in greater smoothing of the time series.

The owners of Hal's Cookie Company have collected sales data for the past 8 months.These data are shown as follows: Using a starting forecast in period 1 of 100,the forecast bias over periods 2-8 is negative when a single exponential smoothing model is used with a smoothing constant of 0.20.

Prior to conducting double exponential smoothing a simple linear regression is conducted and the trend equation is = 42 + 38.3t,so the smoothed constant process value should be C₀ = 38.3 and the smoothed trend value should be T₀ = 42.