Predictive Modeling Using Logistic Regression
Classroom duration: 2.0 days Live Web duration: 4 half-day sessions CEU: 1.2
This course covers predictive modeling using SAS/STAT software with emphasis on the LOGISTIC procedure. This course also discusses selecting variables, assessing models, treating missing values, and using efficiency techniques for massive data sets.
Learn how to
- use logistic regression to model an individual's behavior as a function of known inputs
- handle missing data values
- tackle multicollinearity in your predictors
- assess model performance and compare models.
Who should attend
Modelers, analysts, and statisticians who need to build predictive models, particularly models from the banking, financial services, direct marketing, insurance, and telecommunications industriesPrerequisites
Before attending this course, you should- have experience executing SAS programs and creating SAS data sets, which you can gain from the SAS Programming I: Essentials course
- have experience building statistical models using SAS software
- have completed a statistics course that covers linear regression and logistic regression, such as the Statistics I: Introduction to ANOVA, Regression, and Logistic Regression course.
Course Contents
Predictive Modeling- business applications
- analytical challenges
- parameter estimation
- adjustments for oversampling
- missing values
- categorical inputs
- variable clustering
- variable screening
- subset selection
- ROC curves and Lift charts
- optimal cutoffs
- K-S statistic
- c statistic
- profit
- evaluating a series of models
Software Addressed
This course addresses the following software product(s): SAS/STAT, SAS/GRAPH.Classroom Course Materials
Students receive a hardcopy of the course notes and, in some courses, can choose to take home a copy of the course data.Live Web Course Materials
Students attend Live Web classes using a Web browser and a telephone and interact with their instructor and fellow classmates in real time. Each student receives an e-mail with instructions on how to join the class three business days before the class begins. The instructions e-mail includes a link to download the course materials, including the exercise files. Students need to download and print the course materials prior to class.System Requirements
For Live Web, you must- review and follow the general system requirements.
- complete the course exercises through our virtual lab. The virtual lab allows you to access the software used in class over the Internet, so that you do not need this software on your local machine.
- run this
test to connect to a virtual lab session. If firewall problems prevent you from connecting to the virtual lab, then you will need the following software installed and configured in your environment to participate in the course exercises:
- Base SAS 9.2 or 9.1.3 on a Windows operating system; SAS/STAT software; and SAS/GRAPH software. Please note that a portion of this class covers the new features in SAS 9. Students who are using a release earlier than SAS 9 will not be able to complete approximately 20% of the course exercises.