Forecasting Using SAS Software: A Programming Approach

Duration: 3.0 days

Audience

The course is intended for scientists, engineers, and analysts who have the responsibility of forecasting for their organizations. Students are expected to have some knowledge of analytics coursework such as applied statistics, statistical modeling, or data mining and domain knowledge in an application area such as energy production, manufacturing, or a scientific discipline.

Course Description

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.

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

Forecast Models with Explanatory Variables

ordinary regression models
event models
time series regression models

Software Addressed

This course addresses the following software product(s): SAS/ETS.

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