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Forecasting Using SAS Software: A Programming Approach

 
Obiettivi
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.
a chi è rivolto

Scientists, engineers, and business analysts who have the responsibility of forecasting or evaluating policies and practices for their organizations.

Requisiti
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 Programmazione SAS 1: fondamenti 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 Statistica 2: analisi della varianza e della regressione course.
Argomenti
• 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.
 
 
Formazione
Durata
3 giorni
Quota
1.700,00 Euro + IVA
Questo corso fa parte dei percorsi formativi
SAS Academy
ANALYTICS SERIES
Per informazioni sulle Date del corso contattate il Servizio Formazione.
Tel. 02 8313 41 r.a.
formazione@ita.sas.com