2021
DOI: 10.9734/jpri/2021/v33i51a33468
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Prediction of COVID-19 New Cases Using Multiple Linear Regression Model Based on May to June 2020 Data in Ethiopia

Abstract: The aims of this study was to predict COVID-19 new cases using multiple linear regression model based on May to June 2020 data in Ethiopia. The COVID-19 cases data was collected from the Ethiopia Ministry of Health Organization Facebook page. Pearson’s correlation analysis and linear regression model were used in the study. And, the COVID-19 new cases was positively correlated with the number of days, daily laboratory tests, new cases of males, new cases of females, new cases from Addis Ababa city, and new cas… Show more

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Cited by 1 publication
(2 citation statements)
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“…The correlation coefficient can be used to show the linear relationship between two continuous variables in a multiple linear regression model (Argawu et al 2021). The estimated correlation coefficient formula is as follows:…”
Section: Correlation Coefficientmentioning
confidence: 99%
See 1 more Smart Citation
“…The correlation coefficient can be used to show the linear relationship between two continuous variables in a multiple linear regression model (Argawu et al 2021). The estimated correlation coefficient formula is as follows:…”
Section: Correlation Coefficientmentioning
confidence: 99%
“…Rath et al (2020) predicted active Covid-19 cases in Odisha and India with the Y variable used as the number of active Covid-19 cases in Odisha and India while the X variables used were the number of positive Covid-19 cases, Covid-19 recovery cases, and Covid-19 death cases. Argawu et al (2021) predicted new Covid-19 cases using multiple linear regression in Ethiopia with the Y variable used as the number of new Covid-19 cases in Ethiopia and the X variables used were the number of days, daily laboratory tests, and the number of new patients from Addis Ababa city.…”
Section: Introductionmentioning
confidence: 99%