ISDS 3115 Chapter 4 True/False Questions Exam 1

False

A naïve forecast for September sales of a product would be equal to the forecast for August.

True

A naïve 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 0.78 means that there is a 0.78 unit rise in Y per period.

True

Cycles and random variations are both components of time series.

True

Demand 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

Forecasts may be influenced by a product's position in its life cycle.

False

Forecasts of individual products tend to be more accurate than forecasts of product families.

True

If a forecast is consistently greater than (or less than) actual values, the forecast is said to be biased.

False

In a regression equation where y-hat is demand and x is advertising, a coefficient of determination (R2) 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.

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.

False

Mean squared error and exponential smoothing are two measures of the overall error of a forecasting model.

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.

False

Regression lines graphically depict "cause-and-effect" relationships.

True

Seasonal indices adjust raw data for patterns that repeat at regular time intervals.

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.

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.