

Logistic Regression Modelling (Credit Scoring) using SAS -step by step
Theory, SAS program explanation, SAS output deep dive & interpretation and Model data workout steps
Self paced
tutorials
The course promises to explain concepts in a crystal clear manner. It goes through the practical issue faced by analyst.
Course Package:
- 72 mp4 HD Videos
- 4 Excel File
- 2 Word Document
- 8 PDF Files
Some of the discussion items would be:
- How to clarify objective and ensure data sufficiency.
- How to go for variable selection? How to deal with numeric variables and character variables.
- What is the approach to take when you starting with 1000 variables vs. when you are starting with 150 variables.
- Understanding multi collinearity removal steps and recommendations.
- Understanding step wise regression
- Understanding different section of logistic regression output
- Understand model validation and coefficient stability check
- Understanding the strength of the model - KS, Gini
Course Outline:
Section 1 – Introduction to Model
- Understand what is a model? What is a credit score? What is modelling?
- Where it is used?
- What benefit it brings?
- Discuss various kinds of score / models.
- What makes a typical scorecard
Section 2 – Data design
- Steps of model building
- Understand, terms associated with modelling like historical window, performance period etc.
- Understand, how to select performance window
- Understand about the characteristics, which can be considered, for model building.
- Practical scenarios associated with model design discussion
Section 3 - Data Audit and Treatment
- How to build data for model building
- How to apply exclusions before getting into the data
- Learn data investigation techniques through simple but powerful techniques. The trick lies in getting into the more details and finer prints of the output.
- Proc contents
- Proc print
- Proc means
- Proc freq
- Examining bi-variate plot
Section 4 – Variable selection
- How to go for variable selection
- Different variable selection techniques such as
- Chi Square
- Stepwise Regression
- Info value
- Fishers linear discriminant function
- Cramer's V, Phi Square
- Guidance about, which technique to apply when.
Section 5 – Multi collinearity Treatment
- What is multi collinearity?
- Recommendations about how remove it?
- Understand output of each steps of multi collinearity removal.
- Understand terms associated with the same
- VIF
- Factor loading
- Wald chi square (bi variate and multi-variate)
Section 6 – Iterate for final model development
- How to apply forward / backward stepwise regression
- How to decide about final number of variables in the model
- Deep dive in logistic regression output
- Understanding terms associated with logistic regression output
- Log likelihood ratio
- AIC
- SC
- Concordance
- Somer's D
Section 7 – Validate model
- KS
- Rank ordering
- Gini Statistics
- Coefficient stability
- Scoring
- Model usage guideline
- Model presentation guideline
Keywords:
logistic, logistic regression, logistic regression using SAS, credit scoring, SAS, scoring, modelling, data mining, video course
Language of instruction: English
- Self Paced course including video tutorials and Documents
- Learn model development from basic to advance - step by step
- 10 dedicated videos for various steps of model data workout
- Total 72 mp4 HD videos, 4 excel file, 2 word document and 8 pdf files
- Understand how to apply logistic regression practically
I am Gopal an Analytics professional with 13+ years of professional experience. I am a keen trainer, who believes that training is all about making users understand the concepts. If students remain confused after the training, the training is useless. I ensure that after my training, students (or partcipants) are crystal clear on how to use the learning in their business scenarios. My expertise is in Credit Card Business, Scoring (econometrics based model development), score management, loss forecasting and MS access based database application development.
Schedule & Syllabus
