Forecasting Using SAS® Software: A Programming Approach
FETSP : FETS42
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.
Learn How To
- Build simple forecast models.
- Build advanced forecast models for autocorrelated time series and for time series with trend and seasonality.
- Build forecast models that contain explanatory variables.
- Build models to assess the impact of events such as public policy changes (for example, DUI laws), sales and marketing promotions, and natural or man-made disasters.
Who Should Attend
Scientists, engineers, and business analysts who have the responsibility of forecasting or evaluating policies and practices for their organizations
Prerequisites
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.
- Experience in data analysis and statistical modeling. You can gain the prerequisite knowledge by completing the Statistics 2: ANOVA and Regression course.
- Experience with stationary ARMA models and elementary forecast models like time trend models and exponential smoothing models for forecasting. You can gain this experience by completing the Time Series Modeling Essentials course.
SAS Products Covered
SAS/ETS
Course Outline
Introduction to Forecasting
- Time series and forecasting.
- Introduction to forecasting with SAS software.
- Evaluating forecasts.
- Introduction to stationary time series.
- Automatic model selection techniques for stationary time series.
- Estimation and forecasting for stationary time series.
- Introduction to nonstationary time series.
- Modeling trend.
- Alternatives to PROC ARIMA for modeling trend.
- Seasonal ARIMA models.
- Alternatives to PROC ARIMA for fitting seasonal models.
- Forecasting the airline passengers data.
- Ordinary regression models.
- Event models.
- Time series regression models.
Live Class Schedule
Duration: 21 hours
Step into our live classes and experience a dynamic learning environment where you can ask questions, share ideas, and connect with your instructor and classmates. With on-demand lab hours, you can explore the material at your own pace. Our globally acclaimed instructors will motivate you to think bigger, so you can take what you've learned and achieve your biggest goals.
This course isn't publicly scheduled, but private training and mentoring may be available. Contact us to explore options.
Private Training
Get training tailored specifically for your team, led by expert SAS instructors. Choose from virtual sessions, or training at your location (or ours). Perfect for teams seeking a customized curriculum and plenty of interaction with a SAS specialist. We'll schedule it at a time that works for you.
Mentoring Services
Take your training to the next level with personalized mentoring. While private training offers structured coursework, mentoring provides hands-on, real-time support from a subject matter expert. As you work with your own data, you'll receive expert guidance to help you uncover insights, unlock the full potential of your data, and make faster progress. Perfect for those looking to apply what they’ve learned and see quicker results.