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Analyzing the Impact of Age and Gender on COVID-19 Deaths Using Two-Way ANOVA

DOI: 10.4236/oalib.1109658, PP. 1-17

Subject Areas: Applied Statistical Mathematics, Mathematical Analysis

Keywords: COVID Deaths, Two-Way ANOVA, Post-Hoc ANOVA Test, Tukey HSD Test

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Abstract

Since the start of COVID-19 there have been widely spread notions that men can contract the disease at a higher rate than women and are more likely to die from it. Furthermore, age has been reported as a risk factor in COVID-19 mortality, and a vast majority of COVID-19 deaths have been among elderly people. Therefore, it is interesting to conduct a statistical analysis on COVID-19 deaths to draw conclusions on whether men are more likely to die of COVID-19 than women, and the influence of age groups on the number of reported deaths of COVID-19 and the interaction between these two factors. This paper uses a two-way analysis of variance (two-way ANOVA) as a statistical tool to analyze COVID-19 deaths in the US. Two-way ANOVA can effectively determine whether the age and gender are significant factors in COVID-19 death cases in the US. The dependent variable in the analysis is the number of COVID deaths in the entire US, and the two independent variables are the age groups and gender (sex). The age groups consist of 11 subgroups or levels ranging from babies to elderly people. The sex is either male or female. Results showed that age group is a significant factor in COVID deaths, while gender was found to be insignificant factor in the mortality of COVID.

Cite this paper

Abdulhafedh, A. (2023). Analyzing the Impact of Age and Gender on COVID-19 Deaths Using Two-Way ANOVA. Open Access Library Journal, 10, e9658. doi: http://dx.doi.org/10.4236/oalib.1109658.

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