Time Series and Forecasting

3 credits · Undergraduate

(3 hrs Lecture) The course deals with the general problem of analysing data which is ordered over time, for the purpose of forecasting and statistical prediction. Such data do not represent an independent sample and thus can not be analyzed using other statistical methods. Topics include trend analysis, smoothing by moving averages, seasonal indices; forecasting using exponential smoothing and Box-Jenkins models. Restrictions: Students may not hold credit for this course and STAT-2601. Requisite Courses: STAT-3103 [prerequisite(s)].