Abstract
This paper provides a comprehensive overview of COVID-19 related deaths within India over the first eight months of 2020 for two different Kaggle data sets. Analyzing first data set provided by the Kaggle for the period included Indian Nationality, states, and counts for total cases, deaths, and cured demonstrated that the states are statistically significant in a regression model. Furthermore, the second Kaggle data set provided by the Kaggle for the period for age, gender, nationality, and all states in the country, I drew conclusions concerning correlations between COVID-19 deaths and the four factor categories and found that the overall logistics regression model was statistically significant. I concluded that within the first eight months of 2020, the both sexes are affected equally by the virus while age and states of residence play important roles in life and death due to the virus. Higher urban populated states with higher GDP creation have seen highest virus related deaths and may explain the forced avoidance of social distancing effect.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IP Indian Journal of Immunology and Respiratory Medicine
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
