Statistical modelling
- Present - ()
• Data Description, Data Auditing, Understanding the Business problems.
• Converting business problem into Stats problem.
• Data Cleaning and Preparing for Model building
• Setting up the assumptions.
• Testing the Assumptions (Hypothesis Testing- Anova, Chi Sq. Weight of evidence, Information Value).
• Building the logistic regression model using variable from Correlation matrix.
• Fine tuning of the model.
• As per the business context setting the optimum Value for OCV.
• Validating the Model using AUROC, concordance, discordance, decile analysis, Accuracy specificity and sensitivity.
• Preparing the document about the Model and its Pros and CONs of the Model.