It is well known that the size of initial loans approved by private lending agencies (banks, credit unions etc.) corresponds with the median income of the location of the individual, it also corresponds with gender. We wanted to show if it was the case with the PPP. We use standard machine learning techniques such as Lasso and found statistically significant association between gender of business owner and size of initial loan approvals for the State of Arkansas, and Least Squares Regression and Decision Tree regression to find a somewhat tenuous relationship between median income and initial loan approval amount and finally a strong association with the size of business. This has important applications for the equity of access to credit for marginalized peoples.

The research paper proposes an algorithm to find congruence criteria between two convex polygons in Euclidean Geometry. It begins with a review of triangles, then extends to quadrilaterals and eventually gener- alizes the case to n-sided polygons. It attempts to prove said algorithm using a method of induction and a case-by-case analysis. It also states a corollary to said algorithm