CHAPTER 4: FORECASTING
TRUE/FALSE
1.
A naïve forecast for September sales of a product would be equal to the forecast for August.
False (Timeseries forecasting, moderate)
2.
The forecasting time horizon and the forecasting techniques used tend to vary over the life cycle of
a product.
True (What is forecasting? moderate)
3.
Demand (sales) forecasts serve as inputs to financial, marketing, and personnel planning.
True (Types of forecasts, moderate)
4.
Forecasts of individual products tend to be more accurate than forecasts of product families.
False (Seven steps in the forecasting system, moderate)
5.
Most forecasting techniques assume that there is some underlying stability in the system.
True (Seven steps in the forecasting system, moderate)
6.
The sales force composite forecasting method relies on salespersons’ estimates of expected sales.
True (Forecasting approaches, easy)
7.
A timeseries model uses a series of past data points to make the forecast.
True (Forecasting approaches, moderate)
8.
The quarterly "make meeting" of Lexus dealers is an example of a sales force composite forecast.
True (Forecasting approaches, easy)
9.
Cycles and random variations are both components of time series.
True (Timeseries forecasting, easy)
10.
A naive forecast for September sales of a product would be equal to the sales in August.
True (Timeseries forecasting, easy)
11.
One advantage of exponential smoothing is the limited amount of record keeping involved.
True (Timeseries forecasting, moderate)
12.
The larger the number of periods in the simple moving average forecasting method, the greater the
method's responsiveness to changes in demand.
False (Timeseries forecasting, moderate)
13.
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 (Timeseries forecasting, easy)
14.
Mean Squared Error and Coefficient of Correlation are two measures of the overall error of a
forecasting model.
False (Timeseries forecasting, easy)
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15.
In trend projection, the trend component is the slope of the regression equation.
True (Timeseries forecasting, easy)
16.
In trend projection, a negative regression slope is mathematically impossible.
False (Timeseries forecasting, moderate)
17.
Seasonal indexes adjust raw data for patterns that repeat at regular time intervals.
True (Timeseries forecasting, moderate)
18.
If a quarterly seasonal index has been calculated at 1.55 for the OctoberDecember 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 (Timeseries forecasting: Seasonal variation in data, moderate)
19.
The best way to forecast a business cycle is by finding a leading variable.
True (Timeseries forecasting, moderate)
20.
Linearregression analysis is a straightline mathematical model to describe the functional
relationships between independent and dependent variables.
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 Spring '09
 KITAHARA
 Management, Forecasting, Regression Analysis, Sales, analytic skills, Timeseries forecasting

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