Chap 14 - Exam #3 - T/F
A bias error results from unpredictable factors that cause the forecast to deviate from actual demand.
F
Aggregating products or services together generally decreases the forecast accuracy.
F
Combination forecasting is a method of forecasting that selects the best from a group of forecasts generated by simple techniques.
F
Judgment methods of forecasting are quantitative methods that use historical data on independent variables to predict demand.
F
Judgment methods of forecasting should never be used with quantitative forecasting methods.
F
Market research is a systematic approach to determine consumer interest by gaining consensus from a group of experts while maintaining their anonymity.
F
Random variation is an aspect of demand that increases the accuracy of the forecast.
F
Regression equations with a coefficient of determination close to zero are extremely accurate because they have little forecast error.
F
Salesforce estimates are extremely useful for technological forecasting.
F
The Delphi method is a process of gaining consensus from a group of experts by debate and voting throughout several rounds of group discussion led by a moderator.
F
The closer the value of the sample correlation coefficient is to -1.00, the worse the predictive ability of the independent variable for the dependent variable.
F
The larger the slope of the regression line, the more accurate the regression forecast.
F
The standard error of the estimate measures how closely the data on the independent variable cluster around the regression line.
F
The trend projection with regression model is highly adaptive.
F
A linear regression model results in the equation Y = 15 - 23X. If the coefficient of determination is a perfect 1.0, the correlation coefficient must be -1.
T
A naive forecast is a time-series method whereby the forecast for the next period equals the demand for the current period.
T
A simple moving average of one period will yield identical results to a naive forecast. Answer: TRUE
T
Aggregation is the act of clustering several similar products or services.
T
An exponential smoothing model with an alpha equal to 1.00 is the same as a naive forecasting model.
T
Better forecasting processes yield better forecasts.
T
Bias is the worst kind of forecasting error.
T
Combination forecasting is most effective when the techniques being combined contribute different kinds of information to the forecasting process.
T
Focus forecasting selects the best forecast from a group of forecasts generated by individual techniques.
T
Forecast error is found by subtracting the forecast from the actual demand for a given period.
T
Forecasts almost always contain errors.
T
One of the basic time series patterns is random.
T
Some analysts prefer to use a holdout set as the final test of a forecasting procedure.
T
Technological forecasting is an application of executive opinion in light of the difficulties in keeping abreast of the latest advances in technology.
T
The causal method of forecasting uses historical data on independent variables (such as promotional campaigns and economic conditions) to predict the demand of dependent variables (such as sales volume).
T
The repeated observations of demand for a product or service in their order of occurrence form a pattern known as a time series.
T
The trend projection with regression model can forecast demand well into the future.
T
Time-series analysis is a statistical approach that relies heavily on historical demand data to project the future size of demand.
T
Time-series forecasts require information about only the dependent variable.
T
When a significant trend is present, exponential smoothing forecasts can be below or above the actual demand, and must therefore be modified.
T
