Business Forecasting using SAS®:
A Point-and-Click Approach

Duration:

3 days

Description

This course teaches business analysts how to carry out forecasting projects using the point-and-click interface in the Time Series Forecasting System in SAS/ETS. Course topics include exponential smoothing models, autoregressive integrated moving average models and dynamic regression models.

Prerequisite Skills

Before attending this course you should be able to:

• create and access SAS data sets using the SAS windowing environment or a product such as SAS Enterprise Guide
• have an understanding of statistics. This knowledge can be gained by attending an introductory statistics course, for example,
  Applying Statistical Concepts using SAS
• evaluate quantitative forecasts related to a business problem based on your advanced domain knowledge in an area such as finance, manufacturing or retail.

SAS Modules Used

This course covers SASŪ Time Series Forecasting System SAS/ETS.

Course Topics

Business Forecasting

• introduction to business forecasting
• introduction to time series forecasting
• descriptive and exploratory analysis of time series data.

Simple Forecast Models

• modelling trend
• modelling seasonality
• using indicator variables to model events
• exponential smoothing models with trend components
• exponential smoothing models with trend and seasonal components

Advanced Forecast Models for Stationary Time Series

• autoregressive models
• moving average models
• mixed autoregressive moving average models
• identifying an appropriate autoregressive moving average model
• estimation and forecasting methods

Advanced Forecast Models for Nonstationary Time Series

• using differencing to model trend and seasonality
• trend models
• seasonal models.

Forecast Models with Explanatory Variables

• ordinary regression models
• event models
• time series regression models