Logistic Regression using SAS - Indepth Predictive Modeling

[LeeAndro]

BestSeller | h264, yuv420p, 1280x720 | ENGLISH, aac, 44100 Hz, 2 channels, s16 | 17h 54 mn | 1.36 GB
Instructor: Gopal Prasad Malakar

What is this course all about?

Analytics /Machine Learning / Data Science: Statistical / Econometrics foundation, SAS Program details, Modeling demo What you'll learn

Learn model development

Understand the science behind model development

Understand the SAS program required for various steps

Get comfortable with interpretation of SAS program output

See the step by step model development

Requirements

Basic knowledge of SAS

Description

This course is all about credit scoring / logistic regression model building using SAS. It explains

There course promises to explain concepts in a crystal clear manner. It goes through the practical issue faced by analyst. Some of the discussion item would be

How to clarify objective and ensure data sufficiency?

How do you decide the performance window?

How do you perform data treatment

How to go for variable selection? How to deal with numeric variables and character variables?

How do you treat multi collinerity scientifically?

How do you understand the strength of your model?

How do you validate your model?

How do you interpret SAS output and develop next SAS code accordingly?

Step by step workout - model development on an example data set

What kind of material is included?

It consists of video recording of screen (audio visual screen capture), pdf of presentations, Excel data for workout, word document containing code and Excel document containing step by step model development workout details

How long the course will take to complete?

Approximately 30 hours

How is the course structured?

It has seven sections, which step by step explains model development

Why Take this course?

The course is more intended towards students / analytics professionals to

Get crystal clear understanding

Get jobs in this kind of work by clearing interview with confidence

Be successful at their statistical or analytical profession due to the quality output they produce

Who this course is for:

Students

Analysts / Analytics professional

Modelers / Statisticians



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