Question 1

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 2

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 double 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

The statement is true. Double exponential smoothing involves using an initial constant level and trend value, which can be derived from a linear trend regression model. The intercept can be used for the constant level, and the slope coefficient can be used for the trend value. The smoothing parameters alpha and beta are then used to adjust and refine the forecast based on current and past data.

Question 3

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 puts more weight on recent observations, causing the forecast to respond more quickly to any irregular movements in the data. This results in a less smoothed out forecast compared to a smaller smoothing constant.

Question 4

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

Double exponential smoothing is used when the data shows a trend. If there is no trend in the data, simple exponential smoothing is more appropriate.

Question 5

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

This statement is true. Simple exponential smoothing models rely on a starting point for the first forecast, and this starting point can have a significant impact on the accuracy of subsequent forecasts. Having more data points helps to reduce the impact of a potentially arbitrary starting point.

Question 6

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 7

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 8

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

Accepted Answer

Double smoothing model, also known as Holt's method, uses two smoothing constants: alpha for the level (or the actual data), and beta for the trend component. The second smoothing constant, beta, is introduced to account for any trend that may exist in the data.

Question 9

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

The statement is incorrect. If there is evidence of a linear trend in the data, the company should employ a double or triple exponential smoothing model to account for the trend. A single smoothing model is more appropriate when there is no discernible trend in the data.

Question 10

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 for which a forecast is to be prepared is called the forecasting horizon, which is the time duration for which the forecast is made. Therefore, option A is the correct choice. Option B is not entirely incorrect, but it is an incomplete definition of the forecasting horizon. Option C and D are both incorrect as they are not relevant to the context of the question.

Question 11

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

If the first data point is used as the forecast for period 1 in single exponential smoothing, it is considered the initial or starting point and should not be included when calculating measures of forecast error.

Question 12

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 a forecasting technique involves identifying the characteristics of the data and determining the appropriate model that fits those characteristics. This is called model specification. Model fitting (D) involves estimating the parameters of a specific model while model diagnosis (A) refers to testing the fit of a pre-specified model. Validity checking (C) involves verifying that the forecasting model produces accurate results over time. Therefore, the best choice is B).

Question 13

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

Since the forecast bias is negative, it means that the actual sales are lower than the forecasted sales. However, the question states that a single exponential smoothing model with a smoothing constant of 0.20 is used, but it doesn't provide any information regarding the accuracy of the forecast. Therefore, we can't determine whether the statement is true or false.

Question 14

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

A smoothing constant greater than 0.50 gives more weight to recent observations, which can lead to either positive or negative bias depending on the data trend, not necessarily positive bias in most cases.

Question 15

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 16

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 question states that 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, indicating that the forecast accuracy is worse for the higher values of alpha and beta. Therefore, the statement is true.

Question 17

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 18

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 19

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

Single exponential smoothing is a time series forecasting method that uses one smoothing constant to weigh historical data. It is most appropriate for data that do not exhibit trend or seasonal components.

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 smoothing constant of 0.4,the forecast value for period 3 is 112.

Accepted Answer

The question provides information on the forecast value for period 3 using a smoothing constant of 0.4, which is 112. However, there is no information provided about the actual sales data or the accuracy of the forecast.

Quiz 16: Analyzing and Forecasting Time-Series Data

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

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.

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 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.

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

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:

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

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