# Lecture Notes for MATH 241 - Statistical Applications at St. Mary's (SMC)

## Notes Information

 Material Type: Class Note Professor: Staff Class: MATH 241 - Statistical Applications Subject: Mathematics University: Saint Mary's College Term: Spring 2009 Keywords: ObservationTo at (time)Trend AnalysisObservationsTime IntervalsForecastingAssumptionsWeighted AverageComparisonsBusiness Cycle

## Sample Document Text

Time Series and Forecasting A time seres is a set of observations fYjg of some variable taken at regular time intervals (monthly, quarterly, yearly, etc.). Forecasting refers to using past experience to predict values for the future, which requires summarizing the past experience in some useful way, based on the behavior that is expected to continue and factoring out random variation. The ultimate test of a forecasting method can only be carried out after the time predicted { not very helpful when the prediction is needed { so our comparisons of various methods rely on \How well would this method (if it had been used) have predicted what we (now) know really happened?". Thus we use \prediction error" (exactly the same idea as residu- als in regression) for past time periods and the mean of the squares of the errors to compare the success of di erent methods. Our methods break down (broadly) into two groups 1.) Smoothing methods: the simplest description and prediction with no assumption about pattern...

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