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Problem Statement: Life Insurance Data The dataset belongs to a leading life insurance company

Statistics Dec 01, 2021

Problem Statement: Life Insurance Data
The dataset belongs to a leading life insurance company. The company wants to predict the
bonus for its agents so that it may design appropriate engagement activity for their high performing agents and upskill programs for low performing agents.

Capstone Project: PROJECT NOTES-I-3

The first set of project notes must describe the data and be aligned to the analytical business problem the Capstone Project addresses. It should also include the rationale of the project (why is the problem important and what value will it add to the company). The submission should be of 7 to 10 pages(but not limited to) containing a simple and straightforward depiction of the objective of the project, description of data, Exploratory Data Analysis (EDA) report and the insights from EDA.

Below are the guidelines for the Project Notes-I:

Review Parameters Points
1) Introduction of the business problem 4
a) Defining problem statement  
b) Need of the study/project  
c) Understanding business/social opportunity  
   
2)Data Report 2
a) Understanding how data was collected in terms of time, frequency and methodology  
b) Visual inspection of data (rows, columns, descriptive details)  
c) Understanding of attributes (variable info, renaming if required)  
   
3) Exploratory data analysis 10
a) Univariate analysis (distribution and spread for every continuous attribute, distribution of data in categories for categorical ones)  
b) Bivariate analysis (relationship between different variables , correlations)  
a) Removal of unwanted variables (if applicable)  
b) Missing Value treatment (if applicable)  
d) Outlier treatment (if required)  
e) Variable transformation (if applicable)  
f) Addition of new variables (if required)  
   
4) Business insights from EDA  4
a) Is the data unbalanced? If so, what can be done? Please explain in the context of the business  
b) Any business insights using clustering  (if applicable)  
c) Any other business insights  
   
Total 20

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