Paper Title:The Statistical Tests as Predictive Analysers in Health Care Sector

Abstract

n our day to day chores the medical field generates huge amount of data. The biomedical data is of enormous volume. The variety of the data generated in the health care sector escalates the complexity both in terms of storage and computation. Due to improper structuring and ignorance of effectiveness of this data, this indispensable data goes to trash. This data on proper structuring may lead to a lot of inferences and postulates when duly valued. In our present scenario there exists no means of proper analytics strategy to cluster and evaluate the data generated by the medical sector. This leaves the treasury of data hunts unnoticed and unaccustomed. The solution to the herculean task of addressing the data needs of this problem domain can be brought about only by the gizmo of big data. The needs of huge data storage and complex analytics of the medical sector can be contended with the emerging technology of big data. The various analytical tools that prevail in big data demonstrates to equip us with mysterious new discoveries. The modern clustering analysis may mark the beginning of a new era in the health care sector. The healthcare being the foremost need of our day to day life, big data is the only scope to mark a tremendous change in the medical sector and thus provide mankind an increased lifespan. May not to an increased life span it may provide the precaution as the repeated analysis of various data samples may mark the beginning of identification of new panorama for some life threatening malignant disease. This paper focuses on various sampling tests like ANOVA to prove the effectiveness of the therapy and the varied outcomes across subjects of diversified malignancy of the malady. Further the various statistical tests will incur the proved cogent therapy of treatment for individual syndromes. This involves data mining and knowledge based data discovery to extract the data the k-means clustering algorithms to structuring them and the big data tool (R programming) for statistical analysis. This paper aims at the scope of statistical tools that elevates the guidelines of today’s health care


Keywords:Computation, complexity, storage, analysis, ANOVA tests, statistical tools, k-means clustering, knowledge based data discovery.