2 students give presentations at the Nebraska Conference for Undergraduate Women in Mathematics

January 31, 2014

Allison Smith (actuarial science major) and Caitlin Snyder (mathematics and CS major) represented the department at the Nebraska Conference for Undergraduate Women in Mathematics in Lincoln, Nebraska. 

The Nebraska Conference for Undergraduate Women in Mathematics is open to outstanding undergraduate women mathematicians at all stages of their careers. Students have the opportunity to meet other women who share their interest in the mathematical sciences, and those who have already done research are given an opportunity to present their results. The overall goal is to arm participants with knowledge, self-confidence, and a network of peers to help them become successful mathematicians.
 

Both Allison and Caitlin made presentations regarding research they have conducted while at Xavier.

 

Allison Smith
"Hospital Charge Function Estimation and Study of Some Interactions: A Case Study of Diabetes"

ABSTRACT: In this presentation, the backward elimination regression method is proposed to model ’charges’ for diabetic patients. Although charges and cost functions are related, literature shows that both economic theory-based methods and regression based-methods found in literature have singularly employed modeling the cost function (Business company’s interest). In this study, an interactive multivariate regression method for modeling charges (Patients’ interest) is found. Moreover, various first order interactions among explanatory variables of ’charge’ are investigated.

 

Caitlin Snyder
"Election Mapping, Spatial Analysis"

ABSTRACT: My primary focus will be on mapping political maps through R, a computer program that creates a visual representation of statistical data. I will be discussing my collaboration with students in the “PPP” (Philosophy, Politics & the Public) program to address the question of how political candidates decide where to strategically allocate their resources for campaigning. Many factors go into answering this question. I will demonstrate how to visually map and utilize important data like voter turnout and previous election results. After creating a visual map of the data, I will exhibit how this visual representation is easily manipulated to show the political candidate where their campaigning would be most beneficial to them.