__________ is the amount by which the predicted value differs from the observed value of the time series variable.
a. Mean absolute error.
b. Smoothing constant.
c. Forecast error.
d. Mean forecast error.
Errors in Time Series:
A time series is a sequence of data that is collected at specified time intervals. These data points relate to an underlying model on which the times series is based. When the time series model is used to forecast future values based on the past data errors will always be there.
Answer and Explanation:
Forecast error is the amount by which the predicted value differs from the observed value of the time series variable.
When we compare a forecast value with its observed value there is a difference in values because the time series cannot give a 100% accurate forecast. This difference is the forecast error.
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from Accounting 302: Advanced AccountingChapter 15 / Lesson 4