COVID-19 Infections
COVID-19 has impacted almost everything in the world. Effects of how individuals live, interact, and communicate with one another have been profound. However, governments, workers, epidemiologists, entrepreneurs are planning on how to reopen while at the same time limiting the possibility of contracting the virus. Therefore, there is need to study the pattern under which COVID 19 is spreading in the USA. The knowledge of the trends would be vital in planning of various sectors of the economy and even schools. This paper picks the social theory that the spread of the infections is high in the month of July compared to the month of June ().
A t-test is formulated to test the hypothesis by comparing means of the infections in the months since the first positive case of the virus was detected. The main challenge in solving the statistical questions raised by the hypothesis is the random variation in recorded data due to numerous factors such as travelling. Data recorded for new infections in the month of July and the month of June would be quantitatively measured in terms of frequencies. Therefore, interest lies more in the values rather than the confidence intervals of the data points. Data to solve the hypothesis is credibly available from accredited medical institutions such as Johns Hopkins University of Medicine that provides access to Corona virus testing data and expert analysis.
Surveillance data from Johns Hopkins University indicates that the month of June had the highest recorded positive cases of COVID-19 surpassing the two million mark. Evidence of an increasing trend in infections is reported from John Hopkins University’s data. Therefore, the hypothesis that the month of July could record more positive cases of the virus is accepted. Similar tests can be done to ascertain the states that are likely to witness high infections.
Cited Work