Citation

Material Information

Title:
The Relationship Between Sociodemographics and New COVID-19 Cases
Creator:
Tifour, Medin, Heckman, Souha, Mikayla, Bryan
Publication Date:
Physical Description:
Recording

Notes

Abstract:
Coronavirus is a global health crisis that has affected everyone. Variation in number of cases among continents has led us to explore if certain socioeconomic factors enable a country’s predisposition to new COVID-19 cases. New cases per million is the response variable that is used to measure the influence of socioeconomic characteristics. The method that is used to explore the impact the number of new coronavirus cases per million is analyzing the data through R programming, using the following libraries: tidyverse, tibble, dplyr, and ggplot2. This is an exploratory data analysis on the dataset using our seven explanatory variables to figure out how those impact new coronavirus cases per million residents. New cases per million is used so a country’s population is taken into account. Graphs are utilized to visualize data and make comparisons using linear models and regression. In conclusion, the data will show a universal policy is the best because covid cases aren’t correlated to any socio demographic statistics.
Acquisition:
Collected for Auraria Institutional Repository by the Self-Submittal tool. Submitted by Souha, Mikayla, Bryan Tifour, Medin, Heckman.
Publication Status:
Unpublished

Record Information

Source Institution:
Auraria Institutional Repository
Holding Location:
Auraria Library
Rights Management:
All applicable rights reserved by the source institution and holding location.

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