Forecasting Using SAS Software: A Programming Approach

Duration: 3.0 days Course fee: $2,175 EPTO units: 4.2 CEUs: 1.8

This course teaches analysts how to use SAS/ETS software to create forecasting models, evaluate the model for accuracy, and forecast future values using the model.

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.

Who should attend

Scientists, engineers, and business analysts who have the responsibility of forecasting for their organizations

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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 I: Essentials and SAS Programming II: Manipulating Data with the DATA Step courses. 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 II: ANOVA and Regression course.

Course Contents

Introduction to Forecasting

introduction to SAS Time Series Forecasting software
introduction to statistical time series forecasting
measuring goodness-of-fit and accuracy

Simple Forecast Models

modeling trend
modeling seasonality
using pulse, step, and ramp variables to model events

Advanced Forecast Models for Stationary Time Series

introduction to Box-Jenkins forecasting
autoregressive models
moving average models
mixed autoregressive moving average models
identifying an appropriate autoregressive moving average model
estimation and forecasting methods

Advanced Models for Nonstationary Time Series

the use of differencing to model trend and seasonality
trend models
seasonal models
forecasting the airline passengers data
forecasting with nonstandard date variables

Forecast Models with Explanatory Variables

ordinary regression models
event models
time series regression models
unobserved component models

Software

This course addresses SAS/ETS.

Course Materials

Students receive a hardcopy of the course notes and, in some courses, can choose to take home a copy of the course data.

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