0G09AG – IBM Advanced Statistical Analysis Using IBM SPSS Statistics (V25)

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This course provides an application-oriented introduction to advanced statistical methods available in IBM SPSS Statistics. Students will review a variety of advanced statistical techniques and discuss situations in which each technique would be used, the assumptions made by each method, how to set up the analysis, and how to interpret the results. This includes a broad range of techniques for predicting variables, as well as methods to cluster variables and cases.

Course Length: 2 day(s)

Course Price: $1670 CAD

Available Course Formats:

  • In-class
  • Instructor Led Online
  • Self-Paced Virtual Classroom

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Course: 0G09AG – IBM Advanced Statistical Analysis Using IBM SPSS Statistics (V25)

Course Outline

1. Introduction to advanced statistical analysis
- Taxonomy of models
- Overview of supervised models
- Overview of models to create natural groupings

2. Group variables: Factor Analysis and Principal Components Analysis
- Factor Analysis basics
- Principal Components basics
- Assumptions of Factor Analysis
- Key issues in Factor Analysis
- Improve the interpretability
- Use Factor and component scores

3. Group similar cases: Cluster Analysis
- Cluster Analysis basics
- Key issues in Cluster Analysis
- K-Means Cluster Analysis
- Assumptions of K-Means Cluster Analysis
- Two-Step Cluster Analysis
- Assumptions of Two-Step Cluster Analysis

4. Predict categorical targets with Nearest Neighbor Analysis
- Nearest Neighbor Analysis basics
- Key issues in Nearest Neighbor Analysis
- Assess model fit

5. Predict categorical targets with Discriminant Analysis
- Discriminant Analysis basics
- The Discriminant Analysis model
- Core concepts of Discriminant Analysis
- Classification of cases
- Assumptions of Discriminant Analysis
- Validate the solution

6. Predict categorical targets with Logistic Regression
- Binary Logistic Regression basics
- The Binary Logistic Regression model
- Multinomial Logistic Regression basics
- Assumptions of Logistic Regression procedures
- Testing hypotheses

7. Predict categorical targets with Decision Trees
- Decision Trees basics
- Validate the solution
- Explore CHAID
- Explore CRT
- Comparing Decision Trees methods

8. Introduction to Survival Analysis
- Survival Analysis basics
- Kaplan-Meier Analysis
- Assumptions of Kaplan-Meier Analysis
- Cox Regression
- Assumptions of Cox Regression

9. Introduction to Generalized Linear Models
- Generalized Linear Models basics
- Available distributions
- Available link functions

10. Introduction to Linear Mixed Models
- Linear Mixed Models basics
- Hierachical Linear Models
- Modeling strategy
- Assumptions of Linear Mixed Models


Anyone who works with IBM SPSS Statistics and wants to learn advanced statistical procedures to be able to better answer research questions.


  • Experience with IBM SPSS Statistics (navigation through windows; using dialog boxes)
  • Knowledge of statistics, either by on the job experience, intermediate-level statistics oriented courses, or completion of the Statistical Analysis Using IBM SPSS Statistics (V25) course.

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.