Correlation and Causation in the Perspective of COVID-19: An Empirical Study on Canonical Correlation Analysis

COVID-19 has an immense effect on the Globe, crossing 53,86,95,729 affected in more than 220 nations, with 63,18,093 individuals deceased. Various countries released COVID-19 protocols to enclose its spread to control the pandemic. This research article illustrates the Effect of COVID-19 on aged people (age>50), diabetes individuals, and individuals with smoking habits concerning the cause of death. An attempt has been made to identify the predominant variables for the cause of death due to COVID-19. IBM SPSS statistical tool enabled by Canonical Correlation Analysis (CCA) is used for simulation. Data were gathered from the Kaggle, an open repository for 2020. Based on the results obtained, predictions regarding the Cause and Effect of COVID-19 are discussed.