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Predictive Modeling Using Logistic Regression
This course covers predictive modeling using SAS/STAT software with emphasis on the LOGISTIC procedure.
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Course Description
About Program
Format of Training
Prerequisite
Training Features
Course Curriculum
Course Fees
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ContactCourse Description
Modelers, analysts and statisticians who need to build predictive models, particularly models from the banking, financial services, direct marketing, insurance and telecommunications industries
About Program
This course covers predictive modeling using SAS/STAT software with emphasis on the LOGISTIC procedure. This course also discusses selecting variables and interactions, recoding categorical variables based on the smooth weight of evidence, assessing models, treating missing values and using efficiency techniques for massive data sets.
Format of Training
All the benefits of the classroom without the travel:
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
- A SAS expert at your side.
- Focused learning away from the office
- Networking opportunities
- State-of-the-art facilities
- Electronic course notes downloadable to your device and permission to print
- Business Knowledge Series: in-depth courses on the latest business topics
- We offer Connected Classes! Watch for courses in Cary, New York, Arlington, Dallas and San Francisco that connect remote students via our Live Web classroom.
Train when and where you want
- Eliminate travel costs and time away
- Enjoy award-winning e-Courses
SAS e-Learning courses do not include SAS software. You must have SAS software installed to complete the practice exercises.
Prerequisite
Before attending this course, you should
- have experience executing SAS programs and creating SAS data sets, which you can gain from the SAS Programming 2: Data Manipulation Techniques 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 1: Introduction to ANOVA, Regression, and Logistic Regression course.
This course addresses SAS/STAT software.
Training Features
- use logistic regression to model an individual's behavior as a function of known inputs
- create effect plots and odds ratio plots using ODS Statistical Graphics
- handle missing data values
- tackle multicollinearity in your predictors
- assess model performance and compare models.
Course Curriculum
Predictive Modeling
- business applications
- analytical challenges
Fitting the Model
- parameter estimation
- adjustments for oversampling
Preparing the Input Variables
- missing values
- categorical inputs
- variable clustering
- variable screening
- subset selection
Classifier Performance
- ROC curves and Lift charts
- optimal cutoffs
- K-S statistic
- c statistic
- profit
- evaluating a series of models
Course Fees
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