Chapter 4- Forecasting (T/F)
A naive forecast for September sales of a product would be equal to the forecast for August.
False
Forecasts of individual products tend to be more accurate than forecasts of product families
False
If a quarterly seasonal index has been calculated at 1.55 for the October- December quarter, then raw data for that quarter must be multiplied by 1.55 so that the quarter can be fairly compared to other quarters.
False
In a regression equation where Y is demand and X is advertising, a coefficient of determination (R^2) of .70 means that 70% of the variance in advertising is explained by demand.
False
In trend projection, a negative regression slope is mathematically impossible
False
Mean Squared Error and Coefficient of Correlation are two measures of the overall error of a forecasting model
False
The larger the number of periods in the simple moving average forecasting method, the greater the method's responsiveness to changes in demand
False
The larger the standard error of the estimate, the more accurate the forecasting model
False
A naive forecast for September sales of a product would be equal to the sales in August
True
A time- series model uses a series of past data points to make the forecast
True
A trend projection equation with a slope of .78 means that there is a .78 rise in Y for every unit of time that passes
True
Cycles and random variations are both components of time series
True
Demand cycles for individual products can be driven by product life cycles
True
Demand forecasts serve as inputs to financial, marketing, and personnel planning.
True
Focus forecasting tries a variety of computer models and selects the best one for a particular application
True
Forecast including trend is an exponential smoothing technique that utilizes two smoothing constants: one for the average level of the forecast and one for its trend
True
If a forecast is consistently greater than actual values, the forecast is said to be baised
True
In trend projection, the trend component is the slope of the regression equation
True
Linear- regression analysis is a straight- line mathematical model to describe the functional relationships between independent and dependent variables
True
Many service firms use point- of- sale computers to collect detailed records needed for accurate short- term forecasts
True
Most forecasting techniques assume that there is some underlying stability in the system
True
One advantage of exponential smoothing is the limited amount of record keeping involved.
True
Seasonal indexes adjust raw data for patterns that repeat at regular time intervals
True
The best way to forecast a business cycle is by finding a leading variable
True
The forecasting time horizon and the forecasting techniques used tend to vary over the life cycle of a product
True
The quarterly "make meeting" of Lexus dealers is an example of a sales force composite forecast
True
The sales force composite forecasting method relies on salespersons' estimates of expected sales
True