PMI Exam PMI-SP Topic 2 Question 13 Discussion

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.