This course covers a range of introductory statistical topics and uses SAS software to carry out analysis. Emphasis will be placed on the interpretation of the results.
Statisticians and business analysts who want to use a point-and-click interface to SAS; as well as data analysts, qualitative experts, and others who want an introduction to SAS Enterprise Miner
The schedule of events displayed on this page are for full-time program registration. If interested in part-time programs, please contact SAS India.
This course covers a range of introductory statistical topics and uses SAS software to carry out analysis. Emphasis will be placed on the interpretation of the results. It covers the skills required to assemble analysis flow diagrams using the rich tool set of SAS Enterprise Miner for both pattern discovery (segmentation, association, and sequence analyses) and predictive modeling (decision tree, regression, and neural network models). Ready-to-use procedures handle a wide range of statistical techniques including simple descriptive statistics, data visualization, analysis of variance, regression, categorical data analysis, multivariate analysis, cluster analysis, and non parametric analysis are part of this program
Led by an expert instructor who can virtually look over your shoulder. Discuss, share, exchange ideas with students from different countries
Classroom training options include courses offered in our regional training centers or via our Live Web classroom.
Taught by certified instructors at high-tech facilities across the country
Before attending this course, you should have knowledge in statistics covering p-values, hypothesis testing, analysis of variance, and regression. In addition, you should have at least an introductory-level familiarity with basic statistics and regression modeling.
Previous SAS software experience is helpful but not necessary.
Prerequisite Basic Concepts
Getting Started in Enterprise Guide 7.1
Introduction to Statistics
Analysis of Variance (ANOVA)
Categorical Data Analysis
Accessing and Assaying Prepared Data
Introduction to Predictive Modeling: Predictive Modeling Fundamentals and Decision Trees
Introduction to Predictive Modeling: Regressions
Introduction to Predictive Modeling: Neural Networks and Other Modeling Tools
Introduction to Pattern Discovery