Data Analytics and Visualisation System †Free Samples to Students

Question: Discuss about the Data Analytics and Visualisation System. Answer: Introduction The cost of medical malpractice in the US is very high and exceeds $ 50 billion. Due to this, there is a upward pressure on the health care costs coupled with a higher premium for insurance related to medical malpractice. One of the known health insurance provider in US is the UnitedHealth Group which aims for a better understanding of the claims raised on account of medical malpractice. In order to achieve this objective, claims data for 200 random claimants has been provided which comprises of information related to the claim amount, severity, gender, hiring of private attorney or not, age, marital status presence/absence of insurance coupled with speciality. The given report aims to present the findings of the statistical analysis of the data provided in wake of the specific questions that my manager Edmond Kendrick has raised in the email. Through the requisite statistical analysis, the report would aim to answer the queries raised in relation to the claims data. An overall summary of the claim payment amount has been indicated in Appendix 1. The average or mean claim payment amount has come out to be $ 73,457.49. Also, it is estimated that 50% of provided sample claim amount is lesser than or equal to $72,571.38. Further, the claim value of $ 5,400 seems to have the highest frequency in the sample data. The dispersion of the claim amount values in the sample data seem to be quite high considering that the lowest value of claim amount is $ 1,547 while the highest value of claim amount is $ 228,724. 80. Also, the standard deviation of the claim amount from the mean or average claim value stands at $ 32,178.50. Additionally, it is noticeable that the distribution of the claim amount is not symmetric considering the fact that there are certain claim amounts which are unusually large and hence considered outliers in the provided sample data. With a likelihood of 95%, it can be stated that the average age of the claimants for the population would lie between 42 years and 47 years. The requisite computation for the same is highlighted. With a likelihood of 95%, it can be stated that the mean proportion of claimants with No Insurance for the population would lie between 5.03% and 12.97%. The requisite computation for the same is highlighted. Based on the given claim sample data, it would be appropriate to conclude with 95% confidence that the average claim amount paid by the industry has dropped below $ 77,500. The requisite computation for the same is highlighted. Using the claim severity data presented, it can be stated with 95% likelihood that the study indicating that 75% of the patients fall either in MILD or MEDIUM severity condition continues to be valid for the current year as well. The computation for the same is illustrated. Considering the gender trends in the provided claims data concerning the severity of the claims, it can be inferred that there no significant difference in proportion of male and female patients in the category of "MILD or MEDIUM claims. The relevant computation for the same is illustrated. Also, the given sample data does suggest that the payment amount does tend to depend on the fact whether the claimant is represented by a private attorney or not. This is apparent from the fact that the average claim amount of claimants represented by private attorneys tends to be higher than the corresponding claim amount of claimants not represented by private attorneys. The relevant computation for the same is illustrated. The given data provided on claims does not lend support to the assertion that private attorneys tend to have higher representation for SEVERE claims as compared to MEDIUM claims. Hence, the statement is not valid. The relevant calculations to support the above conclusion are illustrated. The given claims data does not lend support to the assertion that SEVERE claims tend to be higher for Orthopedic surgeon in comparison to other specialists. Infact, the results derived in Appendix 4A tend to highlight that the difference between the SEVERE claims proportion for the two does not show any significant difference and hence can be assumed to be same. The given claims data does not lend support to the assertion that average claim amount for SEVERE claims tend to be higher for Orthopedic surgeon in comparison to other specialists. Infact, the results derived in Appendix 4B tend to highlight that the difference between the SEVERE claims average amount for the two does not show any significant difference and hence can be assumed to be same. Conclusion Based on the above analysis, useful conclusions can be drawn about the claims data. It may be concluded that the average age of the claimants tends to lie between 42 and 47 years. Also, most of these claimants tend to have insurance since only a very small proportion (about 5-12%) does not have insurance. The average claim amount has now dropped below $ 77,500. Further, it can also be concluded that 75% of the claims belong to the MILD or MEDIUM category and hence only 25% of the claims fall in the SEVERE category. Also, there are no gender specific differences between the proportions of MILD or MEDIUM category claims. Besides, it may be also concluded that the average claim amount tends to be higher when a private attorney represents the claimant. However, no significant difference is observed between the representation proportion of MEDIUM and SEVERE claims with regards to private attorney. Also, the assertions regards higher proportion and average claim amount for orthopaedic rela ted SEVERE claims in comparison with other specialists has been found incorrect as no evidence is present for the same.