My Pursuit For A Graduate Degree In Qualitative Research

My pursuit for a graduate degree in statistical and economic modeling at Duke University has been motivated by many factors. In my undergraduate studies, I was fortunate enough to find my passion in statistics and find ways to be heavily involved in the field.

In my first three years of undergraduate studies, I took Statistics I, Statistics II, and Marketing Research, which provided the basic framework for understanding basic statistics. However, in my senior year at Fordham University, I discovered my passion for statistics through an Introduction to Econometrics course taught by Dr. Philip Shaw. With Dr. Shaw's encouragement, I published an economic research paper about MLB free agency in the Fordham Undergraduate Research Journal

Philip Shaw, my Econometrics professor, to write a research paper on MLB free agency for the FURJ. Earlier in the fall semester of 2014, I competed at predictive analytics competition for evaluating potential MLB free agents. I had used many of the teachings from my Introduction to Econometrics course for use in my presentation. Yet, our presentation lacked a definite number to define the exact contract MLB free agents should be receiving. After the competition, Dr. Philip Shaw and Dr. Hooman Estelami provided encouragement to pursue experiment with publishing a research paper, exploring the contract valuations of MLB free agents in the Qualifying Offer

The specific goal of the competition was to create a top ten list of the starting pitchers in free agency based on past performance and future, potential performance. The presentation would be presented amongst a panel of MLB executives in baseball operations. As a part of the Fordham team, I helped to create an individual performance value for pitchers and create measures of prediction for their respective future performance. For the individual performance value, I created a statistic called Earned Runs Prevented Average (ERPA) based on a pitcher's ability to induce strikeouts and groundballs. For an indicator of future performance, I studied Anthony Krautmann's, a professor at DePaul University, research articles on baseball performance over long-term contracts. His studies became the inspiration for the shirk deviation statistic used in our presentation, which gave an indication of a pitcher's consistency over the course of their career. In addition, our team predicted the contracts for each respective player based on previous market behavior in MLB free agency. As the 2015 MLB free agency has progressed, our predictive modeling has proven to be accurate. For example, David Price received a 3 year, opt-out deal at $90 million, which our model nearly predicted at 3 years, $85 million. The experience at The Diamond Dollars Case competition proved