Introduction to IBM SPSS Decision Trees (V19) SPVC
This intermediate course is intended 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.
This is the self paced training version of ""Introduction to IBM SPSS Decision Trees"" classroom course. Introduction to IBM SPSS Decision Trees is a two day self-paced training course that covers the principles and practice of the tree-based decision and regression methods available in IBM SPSS Decision Trees. A general introduction to the features of the IBM 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.
If you are enrolling in a Self Paced Virtual Classroom or Web Based Training course, before you enroll, please review the Self-Paced Virtual Classes and Web-Based Training Classes on our Terms and Conditions page, as well as the system requirements, to ensure that your system meets the minimum requirements for this course.
E-Learning IBM Self-Paced Virtual Class (SPVC)
Preis (exkl. MwSt.)