STA30004: Data Mining & CLAIM Variable With Social Business - IT Assignment Help

Assignment Task

Description of the first dataset
There is data for more than 73000 policies in the data file motor20pct.csv that are associated with 
claims in a particular year. The variables for each of the policies in this data set are explained below:- 
CAR_AGE measures the age of the insured car in years 
DRIVERS measures the number of people who are specified as designated drivers 
EXPOSURE measures the fraction of the year for which the policy was active 
MILEAGE measures the expected mileage travelled in a single year 
PRIMAGE gives the age of the primary driver in years 
TOTAL gives the total amount claimed on the policy in the year 
EXCESS = 0, 75 or 100 indicating the excess claim amount associated with each policy. The insurance  company will not pay out claims below this excess amount. 
USAGE specifies how the car is used (S=only social, SB=strictly business, SC=social and business, 
ST=social and taxi) 
CLAIM=1 if there was at least one claim during the year, 0 otherwise. 
Create a variable called CatClaim set equal to “Yes” when CLAIM=1 and “No” for CLAIM=0.
You will be working with a random sample of 10000 of these policies. Instructions for
generating this sample are provided in Tutorial 1. 
Question 1  
Suggest a list of questions that could be answered using this data in your assignment. Consider the  CLAIM variable as a possible TARGET variable in your models and the total claim amount as a  possible RISK variable, reflecting the risk associated with any claim. 
Question 2
Instructions for this question are provided in Tutorials 2 and 3. 
Summarise your data using descriptive statistics and graphs. Some suggestions are provided below. 
All tables and graphs must be numbered/labelled and discussed/interpreted. 

• i) Produce summary statistics for your data
• i) Boxplots for numeric input variables for claim categories
• ii) Pairs plot for all numeric input variables
• iii) Correlation Plot for all numeric input variables
• iv) Hierarchical Correlation Plot for all numeric input variables
• v) Bar charts for the categorical variables Usage and the claim variable
• vi) Other exciting plots 

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