For two independent Kaggle data sets, this article presents a detailed analysis of COVID-19-related mortality in India for the first eight months of 2020. The states are statistically significant in a regression model, according to the first data set provided by Kaggle for the period, which includes Indian nationality, states, and counts for total cases, deaths, and cured.
Furthermore, I drew conclusions concerning correlations between COVID-19 deaths and the four factor categories using the second Kaggle data set provided by Kaggle for the period for age, gender, nationality, and all states in the country, and found that the overall logistics regression model was statistically significant. The study found that both sexes are equally impacted by the virus in the first eight months of 2020, and that age and state of residence play key roles in life and death owing to the virus. Virus-related mortality have been highest in states with higher GDP production, which may explain the compelled avoidance of the social distancing effect.Author (S) Details
Rohan S. Kulkarni
Dr. DY Patil Medical College, Pune, Maharashtra, India.
View Book :- https://stm.bookpi.org/NFMMR-V10/article/view/3519
No comments:
Post a Comment