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Regression for Predictive Analytics

Course Length - 1 Day

Regression analysis is a statistical tool used to explore and model the relationship among variables. This course provides an overview of regression analysis techniques and their application in SAS/STAT Software.
After this course, attendees will be able to develop, apply, interpret and validate predictive linear and logistic regression models.

 

Audience

This course is designed for statisticians, analysts and health practitioners as an introduction into the application of regression analysis techniques using the SAS System.



Prerequisites

Attendees will need to have a basic knowledge of statistical tests and concepts, such as p-values and confidence intervals. Attendees must be familiar with the SAS programming language to at least Fundamental level. We recommend that attendees have three to six months of regular SAS programming experience to gain the most benefit from this course.

Topics

R1 lntroduction

  • What is Regression Analysis
  • Types of Regression Analysis

R2 Exploratory Data Analysis

  • Introduction
  • Describing Data
  • Normality
  • Correlation Analysis
  • Chi Square Tests

R3 Linear Regression

  • Introduction to Multiple Regression
  • Model Building
  • Goodness of Fit
  • Verification of Assumptions
  • Interpretation

R4 Logistic Regression

  • Introduction to Logistic Regression
  • Model Building
  • Goodness of Fit
  • Verification of Assumptions
  • Interpretation
  • Predicting Outcomes

R5 Using Enterprise Guide (Reference)

  • Introduction to Enterprise Guide
  • Introduction to the Environment
  • Generalised Regression Task