Kursbeskrivning: Time Series Analysis and Forecasting with IBM SPSS Forecasting SPVC

PLEASE DO NOT MAKE TRAVEL ARRANGEMENT FOR THIS SELF PACED VIRTUAL COURSE (SPVC). ONCE YOU ARE ENROLLED IN THIS COURSE, YOU WILL NOT BE ABLE TO CANCEL YOUR ENROLLMENT.

After you receive confirmation that you are enrolled, you will be sent further instructions to access your course material and remote labs. You will then have a 30 day window in which to complete your course. Within this 30 days, you will have 336 hours of elab time. The self-paced format gives you the opportunity to complete the course at your convenience, at any location, and at your own pace. The course is available 24 hours a day, but lab system access is allocated on a first-come, first-served basis. When you are not using the elab system, ensure that you suspend your elab to maximize your hours available to use the elab system. Once you have accessed the course, help is available Monday through Friday; questions will be responded to within 24 hours.

NO EXTENSIONS FOR THIS COURSE WILL BE GRANTED.

This is the self paced training version of "Time Series Analysis and Forecasting with IBM SPSS Forecasting" classroom course. This three-day self-paced trainingcourse 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.

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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.

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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.

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Please refer to course overview.

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• 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

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