Everyone always wants to know what the future value of a company will be. Obviously no one can ever know exactly what will happen to the price of a stock but it is possible to predict its future value by using statistics and modeling. This process consists of taking past values and using them to predict how the price will act in the future. This cannot account for specific events within the market but it helps to decide how to hedge an investment.

As March Madness approaches once again I start to ask why the current ranking system exists in the way it does. A group of unknown people choosing teams matchups using other people rankings with a bit of their own personal bias. I started to look into the other ranking systems, most of them based off matchup statistics. I had heard of KenPom before but never really knew what it was exactly and how it ranked the teams.

Today’s NBA has seen a significant change due to the implementation of advanced statistics. With the power of statistical modeling, teams are able to see what the most productive plays and shots are. This has led to lots of change in playstyle and lineups. The newest example of this is the Houston Rockets. This teams flys in the face of the typical lineup played in professional basketball. Most NBA teams consist of a mix of short and tall players.

Through STAT 385 my abilities within R have increased significantly. I had some experience with R before the class but have become much more capable this semester. Here is some of the code I have written in R. Math Functions Here is a function I wrote to calculate mortgage payments mortgage_num <- function(m, p, r){ outcome <- sum((log((r/((m/p)-r))+1))/log(1+r)) ceiling(outcome) Data Tables This code helps find the confirmed cases of Coronavirus in the US