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.
International Journal of Mathematics Trends and Technology
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