Introduction to IBM SPSS Decision Trees
This course covers the principles and practice of the tree-based decision and regression methods available in SPSS Decision Trees. A general introduction to the features of the SPSS Decision Trees module and an overview of decision tree based methods will be covered. These methods (CHAID, Exhaustive CHAID, CRT and QUEST) are used to perform classification, segmentation and prediction modeling in a wide range of business and research areas. The techniques are discussed and compared, analyses are performed, and the results interpreted.
This intermediate course is for:
- Analysts building prediction or decision models for which many predictor variables of different types may be involved
- Survey and Market researchers who need to perform automated decision or segmentation analysis.
You should have:
- Familiarity with the Windows interface
- Knowledge of basic statistics through regression (topics covered in Statistical Analysis Using SPSS) is very useful.
Those with advanced statistical training in predictive models (for example discriminant, logistic regression covered in Advanced Statistics Using SPSS for Windows or Market Segmentation Using SPSS) will gain more from the seminar.
- Introduction to CHAID Analysis
- Recommendations, Tips and Efficiency
- Regression Trees (C and RT)
- General Features of Decision Trees
- Decision Trees (C and RT)
- Tree-Structured Methods
- Additional Features and CHAID Extensions
- QUEST Analysis