Background: The coronavirus pandemic is arguably the direst issue of 2020, impacting the greater majority of the world’s population. One of the most prominent questions surrounding the COVID-19 pandemic is why there is such a wide distribution of total cases and deaths per countries, even in an adjusted population sample. This paper contains both the correlation and regression analysis showing the relationship between the coronavirus cases and deaths and their corresponding affecting factors. Objective: The study aims to verify several intuitions regarding the factors that impact population-adjusted total cases and total deaths with cross-sectional data of different countries. Methods: This was done by deducing from the correlation regression values as well as other statistical results. All the data utilized in this paper was provided by the Our World in Data database. Results: The statistical results showed that population-adjusted total cases are significantly positively affected by GDP per capita and COVID-19 tests per thousand, however, not as significantly affected by the population density and the population rate of elderlies. They also showed that the population-adjusted total deaths are significantly negatively influenced by population-adjusted hospital beds and GDP per capita but positively influenced by the population rate of elderlies. Conclusion: Through this study, it was revealed that while some results did not align with initial hypothesis in the correlation analysis, with supposedly deterring factors showing positive correlation with either population-adjusted total cases or deaths, they had negative relationships in the regression analysis when other independent factors were contained.