Exam 18: Forecasting

For every forecasting problem, there is one best forecasting technique.

In decomposition of time series data, it is relatively easy to identify cycles and autocorrelation components.

There are no differences in strategic and tactical forecasting. A forecast is a mathematical projection, and its ultimate purpose should make no difference to the analyst.

Which of the following is a possible source of bias error in forecasting?

Given a prior forecast demand value of 230, a related actual demand value of 250, and a smoothing constant alpha of 0.1, what is the exponential smoothing forecast value for the following period?

Bayesian analysis is the simplest way to choose weights for the weighted moving average forecasting model.

In business forecasting, what is usually considered a short-term time period?

A time series is defined in the text as chronologically ordered data that may contain one or more components of demand variation: trend, seasonal, cyclical, autocorrelation, and random.

Forecast error is the same as residuals.

Time series forecasting models make predictions about the future based on analysis of past data.

A central premise of exponential smoothing is that more recent data are less indicative of the future than data from the distant past.

In most cases, demand for products or services can be broken down into several components. Which of the following is not considered a component of demand?

If you were selecting from a variety of forecasting models based on MAD, which of the following MAD values from the same data would reflect the most accurate model?

It is difficult to identify the trend in time series data.

There is one type of seasonal variation.

The weighted moving average forecasting model uses a weighting scheme to modify the effects of individual data points. This is its major advantage over the simple moving average model.

In general, which forecasting time frame is best to detect general trends?

In business forecasting, what is usually considered a long-term time period?

Cyclical influences on demand are often expressed graphically as a linear function that is either upward or downward sloping.

The standard error of the estimate of a linear regression is not useful for judging the fit between the data and the regression line when doing forecasts.