Roy Bower

Roy Bower

Assistant Professor, Mathematics

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Roy Bower attended John Carroll university as an undergraduate student, where he majored in Mathematics and minored in Spanish. Afterwards, Roy continued his education at John Carroll and completed a Master’s degree in Mathematics. During this time, Roy was impacted by a Professor of Statistics and decided to take his education in a new direction. Two years later, Roy graduated from Villanova University with a Master’s degree in Applied Statistics. Over this period, Roy had opportunities to teach courses in both Calculus and Statistics and soon realized he had a passion for teaching in a liberal arts setting. This motivated Roy’s decision to next attend the University of South Carolina in pursuit of a Ph.D. After completing a Master’s degree in Statistics, Roy graduated from the College of Public Health at USC with a Ph.D. in Biostatistics in December 2016. Before coming to Furman University in August 2019, Roy was an Assistant Professor of Statistics at Xavier University in Cincinnati, Ohio. Over Roy’s professional career he developed an interest in mentoring student research projects, collaborating with colleagues, and implementing different teaching techniques. Lastly, as a new faculty member with a background in Statistics, Roy is very excited to promote this ever growing and popular field of study within the Furman Math Department and the greater Furman community.​​

Education
​Ph.D.
University of South Carolina
M.S.
University of South Carolina; Villanova University; and John Carroll University
B.S.
John Carroll University

Roy’s professional activity is divided between collaboration and methodological research. Over the past two years, Roy has used his Statistics background as a means to collaborate on a variety of projects with Biologists, Environmental Scientists, Occupational Therapists, and Sociologists. This has led to publications in the Sociology of Sport Journal and the Journal of Occupational Therapy Education. Roy looks to maintain these important relationships and to expand his collaborate effort in order to demonstrate how Statistics can be used to solve a variety of problems from a variety of disciplines. Roy is also very interested in getting students involved in some of these interdisciplinary projects that could potentially lead to summer research and/or publications for the students. In addition to Roy’s effort to collaborate with colleagues from other disciplines, he also maintains an active methodological research agenda. He has published papers that focus on comparing the type one error rate and power between the score, Wald, and likelihood ratio tests in a bivariate setting. Furthermore, Roy’s research advocates using score tests for testing independence between two outcome variables for a variety of bivariate distributions, particularly in small samples. Deriving a score test for independence is of practical importance since assuming responses are not correlated when in reality this may not be true could result in misleading real world conclusions. Roy’s research is ongoing!​

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