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0A028G – Introduction to Time Series Analysis Using IBM SPSS Modeler (V18.1.1)

Home / 0A028G – Introduction to Time Series Analysis Using IBM SPSS Modeler (V18.1.1)

This course gets students up and running with a set of procedures for analyzing time series data.  Students will 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 students will also learn how to specify their own custom models, and also how to identify ARIMA models themselves using a variety of diagnostic tools such as time plots and autocorrelation plots.

Course Outline:

Course Outline

1: Introduction to time series analysis

- Explain what a time series analysis is
- Describe how time series models work
- Demonstrate the main principles behind a time series forecasting model

2: Automatic forecasting with the Expert Modeler

- Examine fit and error
- Examine unexplained variation
- Examine how the Expert Modeler chooses the best fitting time series model

3: Measuring model performance

- Discuss various ways to evaluate model performance
- Evaluate model performance of an ARIMA model
- Test a model using a holdout sample

4: Time series regression

- Use regression to fit a model with trend, seasonality and predictors
- Handling predictors in time series analysis
- Detect and adjust the model for autocorrelation
- Use a regression model to forecast future values

5: Exponential smoothing models

- Types of exponential smoothing models
- Create a custom exponential smoothing model
- Forecast future values with exponential smoothing
- Validate an exponential smoothing model with future data

6: ARIMA modeling

- Explain what ARIMA is
- Learn how to identify ARIMA model types
- Use sequence charts and autocorrelation plots to manually identify an ARIMA model that fits the data
- Check your results with the Expert Modeler

Course Audience & Prerequisites:

Audience

This course is for Business Analyst and Data Scientist. Specifically, this is an introductory course for:

  • Anyone who is interested in getting up to speed quickly and efficiently using the IBM SPSS Modeler forecasting capabilities.

Prerequisites

  • Familiarity with the IBM SPSS Modeler environment (creating, editing, opening, and saving streams).
  • General knowledge of regression analysis is recommended but not required.

Course Offerings:

Instructor Led In Classroom

Newcomp can directly deliver  IBM Business Analytics courses for Business Intelligence, Performance Management, and IBM Advanced Analytics through the use of in-class training facilities.

Currently,  in-class courses are offered in Markham, Ottawa, Vancouver, Halifax, and Edmonton. Please note that classes can be added to new areas based on demand.

Instructor Led Online

Students receive the same quality as an in-class course, with a live instructor and the ability to participate in hands-on labs through real-life examples

ILOs help cut costs by reducing time and travel as they can be taken from home or the office and require only the use of a computer, high-speed wired internet and a headset.

Self Paced

Students can receive the same high-quality training, with the same courseware at their own speed and schedule with SPVC.  Individuals with busy schedules can complete a course over a 30-day timeframe at a lower price than in-class or ILO courses. Please note that there is no live interaction with an instructor in this format.

  • Course Outline
  • Course Audience & Prerequisites
  • Course Offerings
  • Related Courses

Course Outline

1: Introduction to time series analysis

- Explain what a time series analysis is
- Describe how time series models work
- Demonstrate the main principles behind a time series forecasting model

2: Automatic forecasting with the Expert Modeler

- Examine fit and error
- Examine unexplained variation
- Examine how the Expert Modeler chooses the best fitting time series model

3: Measuring model performance

- Discuss various ways to evaluate model performance
- Evaluate model performance of an ARIMA model
- Test a model using a holdout sample

4: Time series regression

- Use regression to fit a model with trend, seasonality and predictors
- Handling predictors in time series analysis
- Detect and adjust the model for autocorrelation
- Use a regression model to forecast future values

5: Exponential smoothing models

- Types of exponential smoothing models
- Create a custom exponential smoothing model
- Forecast future values with exponential smoothing
- Validate an exponential smoothing model with future data

6: ARIMA modeling

- Explain what ARIMA is
- Learn how to identify ARIMA model types
- Use sequence charts and autocorrelation plots to manually identify an ARIMA model that fits the data
- Check your results with the Expert Modeler

Audience

This course is for Business Analyst and Data Scientist. Specifically, this is an introductory course for:

  • Anyone who is interested in getting up to speed quickly and efficiently using the IBM SPSS Modeler forecasting capabilities.

Prerequisites

  • Familiarity with the IBM SPSS Modeler environment (creating, editing, opening, and saving streams).
  • General knowledge of regression analysis is recommended but not required.

Instructor Led In Classroom

Newcomp can directly deliver  IBM Business Analytics courses for Business Intelligence, Performance Management, and IBM Advanced Analytics through the use of in-class training facilities.

Currently,  in-class courses are offered in Markham, Ottawa, Vancouver, Halifax, and Edmonton. Please note that classes can be added to new areas based on demand.

Instructor Led Online

Students receive the same quality as an in-class course, with a live instructor and the ability to participate in hands-on labs through real-life examples

ILOs help cut costs by reducing time and travel as they can be taken from home or the office and require only the use of a computer, high-speed wired internet and a headset.

Self Paced

Students can receive the same high-quality training, with the same courseware at their own speed and schedule with SPVC.  Individuals with busy schedules can complete a course over a 30-day timeframe at a lower price than in-class or ILO courses. Please note that there is no live interaction with an instructor in this format.