What forecasting method would your project use if your project customer requires an
autoregressive moving average for performance forecasting?

A.
Judgmental methods

B.
Time series method

C.
Ensemble forecasting

D.
Causal/econometric method

Explanation:
The autoregressive moving average is an example of a causal/econometric method for the
forecasting project performance. The casual/econometric forecasting method uses the assumption
that it is possible to identify the underlying factors, which might influence the variable being
forecasted. For example, sales of umbrellas might be associated with weather conditions. If the
causes are understood, projections of the influencing variables can be made and used in the
forecast. Some examples of casual/econometric forecasting method are as follows: Regression
analysis using linear regression or non-linear regression Autoregressive moving average (ARMA)
Autoregressive integrated moving average (ARIMA) Econometrics
Answer option B is incorrect. The time series method relies on the earned value, moving average,
extrapolation, and growth curve.
Answer option A is incorrect. The judgmental methods use intuition, the Delphi method, and
forecast by analogy.
Answer option C is incorrect. The ensemble forecasting is not part of the causal/econometric
method for forecasting.