The team is targeting at the following issues: - The team wants to analyze each variable of the data collected through data summarization to get a basic understanding of the dataset and to prepare for further analysis. - As mentioned earlier, a unique page view represents the number of sessions during which that page was viewed one or more times. A visit counts all instances, no matter how many times the same visitor may have been to your site. So the team needs to know whether the unique page view value depends on visits. - Find out the probable factors from the dataset, which could affect the exits. Exit Page Analysis is usually required to get an idea about why a user leaves the website for a session and moves on to another one. Please keep in mind that exits should not be confused with bounces. - Every site wants to increase the time on page for a visitor. This increases the chances of the visitor understanding the site content better and hence there are more chances of a transaction taking place. Find the variables which possibly have an effect on the time on page. - A high bounce rate is a cause of alarm for websites which depend on visitor engagement. Help the team in determining the factors that are impacting the bounce.

After understanding the data, you need to help the committee with the following by the use of the R tool: - The committee is interested to know each field of the data collected through descriptive analysis to gain basic insights into the data set and to prepare for further analysis. - The total value of payment by an insurance company is an important factor to be monitored. So the committee has decided to find whether this payment is related to number of claims and the number of insured policy years. They also want to visualize the results for better understanding. 3 | P a g e - The committee wants to figure out the reasons for insurance payment increase and decrease. So they have decided to find whether distance, location, bonus, make, and insured amount or claims are affecting the payment or all or some of these are affecting it. - The insurance company is planning to establish a new branch office, so they are interested to find at what location, kilometer, and bonus level their insured amount, claims, and payment get increased. (Hint: Aggregate Dataset) - The committee wants to understand what affects their claim rates so as to decide the right premiums for a certain set of situations. Hence, they need to find whether the insured amount, zone, kilometer, bonus, or make affects the claim rates and to what extent.

The goals of this project are: 1. To record the patient statistics, the agency wants to find the age category of people who frequent the hospital and has the maximum expenditure. 2. In order of severity of the diagnosis and treatments and to find out the expensive treatments, the agency wants to find the diagnosis related group that has maximum hospitalization and expenditure. 3. To make sure that there is no malpractice, the agency needs to analyze if the race of the patient is related to the hospitalization costs. 4. To properly utilize the costs, the agency has to analyze the severity of the hospital costs by age and gender for proper allocation of resources. 5. Since the length of stay is the crucial factor for inpatients, the agency wants to find if the length of stay can be predicted from age, gender, and race. 6. To perform a complete analysis, the agency wants to find the variable that mainly affects the hospital costs

This is my first project in R, i have taken help from kaggle also