Logistic Regression with R

R Tutorial 16.0

Vinod and I had struggled a lot to learn Logistic Regression in my time, but then we decided one thing that we would ensure no one struggles too much to learn about it. Hence we wrote a series of articles to explain it and covered the theory of Logistic model along with model building on SAS, let's now understand the same with R.

An Explicit coverage on ROC curve

One of the most trending interview questions from Logistic Regression is "What do you understand by ROC Curve?". Initially I was scared of any question related to ROC curve in my interviews because the concept was always quite confusing for me. So, I finally decided to battle it out by understanding it to the depth.
Now after understanding it thoroughly, I think it is one of the most interesting topics when it comes to logistic Regression. I am sharing all my understanding on ROC curve through this blog. I hope it would make your learning much more rich.

Concordance was never so simple to understand !

Human race has come a long way on the journey of evolution. We are now capable of doing everything that we used to think "God's job" earlier. Yet, I am unable to understand with such a evolved mind, how come people on  earth find it difficult to understand the concept of concordance !

Chill guys ! I was just warming you up to be ready to understand the concept and calculation of Concordance, Discordance, C Stats and other stats in Logistic Regression.

So be ready for it. Believe me you would never be confused with term concordance ever again ?

What do beta coefficients of Logistic Regression say ?

N number of statistical tools are available in market for making our life easy. One click and a super complex model on enormous data is prepared within nanoseconds.

However, no software is yet available  to translate these high end mathematical models into business insights… except one ...

Yes, Human mind !

Would you like to program your mind so that it can translate Logistic Regression model full of betas into layman and business language ? 

Variable reduction technique for Logistic Regression

Variable reduction and Binning using WOE and IV 

It is a beautiful method of variable reduction for a Logistic Regression even before modeling starts. It helps you do a mathematically optimized binning of variables that would help you segregate 1 and 0 best. Interested ? ... then go ahead !
it is also one of most favorite question of interviewers ... so be little more attentive.

Logistic Regression - Part 3 - Result Interpretation

How to interpret the SAS output of Proc Logistic ?

Once we run Proc Logistic in SAS with various options illustrated in previous article "Logistic Regression - Part 2 - How to do it ?" , it gives various tables in the output window.

which of all those tables are important and what do those tables convey? How to check if the model is good or not so good ? Let's learn it in this article .

Logistic Regression - Part 2 - How to do it ?

Learn Proc Logistic in SAS

This article has been written in continuation of our previous article "Logistic Regression - Part 1 - Theory". Please go though the Part 1, before this. This article covers the "How to do" part of Logistic Regression and SAS code explanation.

Logistic Regression - Part 1 - Theory

In the Movie Matrix, while sentiment machines captured the world with a "Matrix" designed with a binary logic (1 and 0) and Morpheus found out Neo and made him learn about it and finally Neo deciphered the Matrix.

Logistic Regression is the NEO of Analytics; so whenever, we have a business question having binary responses (Yes / No, Will Buy it / Won't buy it .... i.e. 1 and 0), and we need to understand the pattern of these 1 and 0s, it is going to be our Saviour.