Forecasting Using SAS Software: A Programming Approach
This course teaches analysts how to use SAS/ETS software to diagnose systematic variation in data collected over time, create forecast models to capture the systematic variation, evaluate a given forecast model for goodness-of-fit and accuracy, and forecast future values using the model. Topics include Box-Jenkins ARIMA models, dynamic regression models, and exponential smoothing models.
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Who should attend
Before attending this course, you should have experience using SAS to enter or transfer data and to perform elementary analyses, such as computing row and column totals and averages, and producing charts and plots. You can gain this experience by completing the SAS Programming 1: Essentials course. Knowledge of SAS Macro language programming is useful, but not required. A student with no experience in data analysis and statistical modeling can gain the prerequisite knowledge by completing the Statistics 2: ANOVA and Regression course.
This course addresses SAS/ETS software.
Introduction to Forecasting