Abstract
Given the socio-economic impact of coronavirus disease 2019 (COVID-19), it is essential to gauge the spread of this disease. Pakistan is one of the countries, which initially did not suffer from this disease. To observe prediction of COVID-19 cases in Pakistan, the study would utilize a linear regression model. By this model, we can predict the number of infected cases in Pakistan in an efficient way. Linear regression and correlation are two parameters used in the estimation of the linear relationship between various parameters. Correlation tells about the direction and strength of an intervariable linear relationship without discrimination between dependent and independent variables (daily COVID-19 infections are the independent variable, and prediction value is the dependent variable). While linear regression explains the estimations that can predict the values based on given information (number of infected and number of prediction) and consider dependent and independent variables. A scatter plot is deemed to be a useful tool in the determination of relationship strength between relative variables. A correlation coefficient is the measure of association with numerical configuration between two comparable variables that can stand between [-1, 1]. By using this linear regression model, we can predict the number of cases in Pakistan.
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