Introduction to Time Series Analysis Using IBM SPSS Modeler (v18.1.1) gets you up and running with a set of procedures for analyzing time series data. Learn how to forecast using a variety of models, including regression, exponential smoothing, and ARIMA, which take into account different combinations of trend and seasonality. The Expert Modeler features will be covered, which is designed to automatically select the best fitting exponential smoothing or ARIMA model, but you will also learn how to specify your own custom models, and also how to identify ARIMA models yourself using a variety of diagnostic tools such as time plots and autocorrelation plots.
Who is it for?
This course is aimed for business analysts and data scientists. It is also intended as an introductory course for anyone who is interested in getting up to speed quickly and efficiently using the IBM SPSS Modeler forecasting capabilities.
What should I have?
Familiarity with the IBM SPSS Modeler environment (creating, editing, opening, and saving streams). General knowledge of regression analysis is recommended but not required
Our trainer is an experienced IBM-SPSS Statistics and DataMining Consultant
Refreshments and course notes included
1: Introduction to time series analysis
2: Automatic forecasting with the Expert Modeler
3: Measuring model performance
4: Time series regression
5: Exponential smoothing models
6: ARIMA modeling
*Disclaimer: Kindly note the scheduled dates below are tentative and are therefore subject to change. Please, do register your interest as we are taking provisional bookings.