All of the following are true about time series methods EXCEPT a. they discover a pattern in historical data and project it into the future. b. they involve the use of expert judgment to develop forecasts. c. they assume that the pattern of the past will continue into the future. d. their forecasts are based solely on past values of the variable or past forecast errors.

A time series is a series of events that is spaced equally in time. It is a statistical technique used to identify a time based trend of events and them make forecast using data from the trend/time series.

Time series requires certain processes which include discovering of a pattern in the historical data, projection of the historical data into the future, assumption that the pattern will remain the same(constant) as the time goes by, etc.

In time series method, since historical data is the point of reference for making a forecast, no expert judgements is required to develop forecasts. This is because once the data of the series from the past has been taken and a trend/pattern has been identified, that becomes the basis for future forecasts.

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