Submitting Campus
Daytona Beach
Department
Mathematics
Document Type
Article
Publication/Presentation Date
11-2020
Abstract/Description
In an application of the mathematical theory of statistics, predictive regression modelling can be used to determine if there is a trend to predict the response variable of social distancing in terms of multiple predictor input “predictor” variables. In this study the social distancing is measured as the percentage reduction in average mobility by GPS records, and the mathematical results obtained are interpreted to determine what factors drive that response. This study was done on county level data from the state of Florida during the COVID-19 pandemic, and it is found that the most deterministic predictors are county population density along with median income.
Publication Title
International Journal of Mathematics Trends and Technology
DOI
https://doi.org/10.14445/22315373/IJMTT-V66I11P504
Publisher
Seventh Sense Research Group
Scholarly Commons Citation
Smith, T. A., Boquet, A. J., & Chin, M. V. (2020). A Statistical Learning Regression Model Utilized To Determine Predictive Factors of Social Distancing During COVID-19 Pandemic. International Journal of Mathematics Trends and Technology, 66(11). https://doi.org/10.14445/22315373/IJMTT-V66I11P504
Included in
Epidemiology Commons, Immunology and Infectious Disease Commons, Statistics and Probability Commons
