Forecasting Using SAS® Software: A Programming Approach
Durchgeführt von Dr. Mihai Paunescu, Senior Analytics Consultant, SAS Austria.
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.Lernen Sie, wie Sie / Learn how to
Zielgruppe / Who should attendScientists, engineers, and business analysts who have the responsibility of forecasting or evaluating policies and practices for their organizations
This course is also offered outside the Advanced Analytics Course Series. Please look here for further information.
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® Programmierung 1: Grundlagen 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.
In diesem Kurs wird mit folgenden Software Modulen gearbeitet: SAS/ETS Software
Introduction to Forecasting