This course combines: SAS Enterprise Guide - ANOVA, Regression and Logistic Regression and Applied Analytics using SAS Enterprise Miner.
This first part of the course is designed for SAS Enterprise Guide users who want to perform statistical analyses.
The second part of his course 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).
Learn how to
- generate descriptive statistics and explore data with graphs
- perform analysis of variance
- perform linear regression and assess the assumptions
- use diagnostic statistics to identify potential outliers in multiple regression
- use chi-square statistics to detect associations among categorical variables
- fit a multiple logistic regression model.
- define a SAS Enterprise Miner project and explore data graphically
- modify data for better analysis results
- build and understand predictive models such as decision trees and regression models
- compare and explain complex models
- generate and use score code
- apply association and sequence discovery to transaction data
- use other modeling tools such as rule induction, gradient boosting, and support vector machines.
Who should attend
Statisticians, business analysts, data analysts, qualitative experts, and others who want an introduction to SAS Enterprise Miner and statistics with SAS Enterprise Guide.
Before attending this course, you should
- be familiar with basic statistical concepts
- have completed an undergraduate course in statistics covering p-values, hypothesis testing, analysis of variance, and regression.