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Applied Statistical method for Biomedical Analytics

Indiana State is interested in understanding the COVID-19 patients’ with respect to its Severity, Mortality, Comorbidities and parameters from March to September 2020. They have access to Patient data from different Hospitals and testing centers. They have arranged the data in four data tables (Table1, Table2, Table3, Table4).

Assume you are a Lead Data Scientist in the State. The State Chief Medical Officer contacts you with request to help them with the [login to view URL] this work you hire 3 Master’s students. Using the help of these students design the methodology that can help the STATE to understand the COVID-19 patients’ in regards to its Severity, Mortality, Comorbidities and Parameters.

Table 1: Patient ID, Gender, Birth Date, Race, Parents Alive, Siblings, Education, Income, Alcoholic/Non-alcoholic, Smoker/Non-Smoker, County, Children going to school, Home Zipcode, Date Tested for COVID, Survival

Table 2: Patient ID, Oxygen Level, Blood Pressure, Glucose, HbA1C, Basophil Count, Neutrophil Count, Monocyte Count, Albumin, CRP, Protein, Creatinine, eGFR, Pulse, Cholesterol, Weight, Height, Hgb, Lymphocyte Count, Co2 level, Albumin

Table 3: Patient ID, Type 2 Diabetes Diagnosed date, Cancer Diagnosed Date- Cancer Name, Autoimmune Disease Diagnosed Date- Autoimmune Disease Name, Neurodegenerative Disease Diagnosed Date- Disease Name, COPD diagnosed Date, Other Disease

Table 4: Patient ID, Restaurant Last visited- Name/Zipcode of Restaurant, Living Near Highway, Work from home, Going to Work-Zipcode, Stay at Home Order date start, Stay at Home Order date end, Stage of Lock down, Park visited day- Name/Zipcode of park, Grocery Store visited- Name/Zipcode, Gas Pump Visit Date- Zipcode.

You have to write the process of analysis in detail. There is no data to analyze.

HINT: This is an open-ended task- Design your question/questions, hypothesis/hypotheses, data exploration/imputation, Test to be carried out, Conclusion.

Skills: Statistics, Biometrics, R Programming Language, Statistical Analysis, Data Processing

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