0G096: Time Series Analysis and Forecasting with IBM SPSS Forecasting
DURATION: 3 Days
SCHEDULED DATES: TBD – Contact Us for more Information
DESCRIPTION
This three-day course gets you up and running with a set of procedures for analyzing time series data. Learn how to forecast using a variety of models which take into account different combinations of trend, seasonality and prediction variables. The new Expert Modeler features in SPSS Trends 14.0 will be covered in this course. Generate predicted values along with standard errors, confidence intervals and residuals. This course will emphasize the graphical display of your results so you can visualize your forecasting models.
AUDIENCE
This advanced course is for
– SPSS users who are interested in getting up to speed quickly and efficiently using the SPSS forecasting capabilities.
– Those who want to know the full capabilities of the Trends module and its Expert Modeler.
PREREQUESITES
You should have:
– On the job experience with SPSS for Windows or completion of the Basics and/or Intermediate SPSS for Windows courses.
– No previous forecasting experience required.
– For users of SPSS for Windows Base System, SPSS Trends.
– It would be helpful to have a basic understanding of regression analysis.
OBJECTIVES
The basics of forecasting
Smoothing time series data
Outliers and error in time series data
Automatic forecasting with the Expert Modeler
Assessing model performance
Fitting curves to time series data
Regression with time series data
Exponential smoothing models
ARIMA models
Applying a model to new data
Seasonal decomposition
Modeling seasonality
Intervention analysis
Transfer functions in ARIMA
Automatic forecasting of several time series
