Vaccination Analysis Abstract

This research paper aims to use the open-source data around us, analyse it and turn the data into useful information. Information like the number of daily vaccinations can be used estimate the number of people going in the following days using Poisson distribution. In a perfect world, that would have been enough and the number of people showing up everyday would equal the known average. Unfortunately, we will need to include a margin of safety also called the confidence interval. Furthermore, a method of approximation will be used for efficiency in computations. The second part of the paper will introduce python-plotted graphs, in order to find patterns or correlation between data(All data manipulation and processing will be done by and on python). We are looking for grouped points hinting at a relationships between our variables, Covid test per thousands people and GDP per capita in USD. This relationship can than be represented by a line and we can use that same line to estimate or predict the amount of covid test taken given a country GDP. In addition to finding the best fit line, concepts concerning curve spread will be used, such as, Variance, Covariance and Mean.