About this Course

Duration 2 Days

This course introduces SAS Visual Statistics for building predictive models in an interactive, exploratory way. Exploratory model fitting is a critical step in modeling big data. This course is appropriate for users of SAS Visual Analytics 7.2 and 7.3.


Before attending this course, you should have an understanding of regression and logistic regression analysis for predictive modeling. You can gain this knowledge from the Statistics 1: Introduction to ANOVA, Regression, and Logistic Regression course. You should also have experience using SAS Visual Analytics, which you can gain from the SAS Visual Analytics: Getting Started course.

This course addresses SAS Visual Statistics software.

Who should attend

Predictive modelers, business analysts, and data scientists who want to take advantage of SAS Visual Statistics for highly interactive, rapid model fitting

Delegates will learn how to

use SAS Visual Statistics to

  • perform statistical analysis of data of any size
  • create a project
  • determine useful preferences and settings
  • create segments, or clusters, of input variables
  • perform regression and logistic regression modeling
  • perform decision tree modeling
  • perform stratified model fitting
  • compare models
  • generate score code.


Introduction to SAS Visual Statistics

Cluster Segmentation

  • segmentation concepts
  • cluster analysis
  • data management

Models with Continuous Targets

  • managing projects and models
  • linear regression models
  • generalized linear models

Models with Categorical Targets

  • logistic regression
  • decision trees

Model Comparison and Assessment

  • comparing models
  • scoring

2 Days


This is a QA approved partner course

Delivery Method

Delivery method


Face-to-face learning in the comfort of our quality nationwide centres, with free refreshments and Wi-Fi.

Find dates and prices

Online booking is currently not available for this course, to find out more please call us on 0113 220 7150 or email us at info@qa.com to discuss how we can help.

Trusted, awarded and accredited

Fully accredited to ensure we provide the highest possible standards in learning

All third party trademark rights acknowledged.