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Retail - Order Return Predictive Model

Training Overview

Predictive Modeling is epitome of analytics applications and great demand in the market. Analyst with Predictive Modeling skills and experience offer significantly better salary package.  Predictive Model Development using Logistics Regression and SAS/R are most commonly used combinations in the organizations.   

Some of the common applications are


  •        Credit Score Development for the Bank (for Credit Card, Personal Loan etc)

  •        Propensity Model for Marketing Campaigns (Cross Sell and Retention)

  •         Churn Prediction in Telecom

  •         Fraud Detection


Training Content


Predictive Model Development using SAS/Rand Logistic Regression Training is designed to take the participants through a well-structured step by step process of Predictive Model development process.Aim is to help you build experience of model development and not just knowing logistic regression. For each stage of Predictive Model development, diverse set of examples will be discussed so that you are aware of challenges,perspective and practical solutions. The training program will cover theoretical background of Logistic Regression and each stage of Predictive Modeling Framework. 


  •         Logistic Regression and Predictive Model

  •         Predictive Model Framework

  •         Defining Target Variables

  •         Creating Independent Variables

  •         Multicollinearity and Model Statistics

  •         Interpreting Logistic Regression output

  •         Predictive Model – Samples and Model Selection


Data Sample/Scenario: Retail Order Return Scenario data is considered for Predictive Model development.

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