Students Present at Mathematics Conference
By Katherine Haines ’21, ’22
Arcadia Computer Science and Mathematics students presented at the spring conference of the regional section of the Mathematics Association of America, which was held online this year.
Erik Edward ’21 and Kody Ream ’21, with support from Luke Thatcher ’21, presented “A Monte Carlo analysis comparing ANCOVA, gain scores, and post-test only methodologies.” Three common techniques for analyzing pretest-posttest designs involving one control and one treatment group are: t-test comparing post-test scores only, t-test comparing gain scores, and analysis of covariance. In this presentation, students gave the results of their simulations, which indicated that the relative power of the techniques is a function of the pretest/posttest correlation coefficient.
Carly Flickinger ’22, Emily Lucy ’21, and Annabelle Rogers ’22, with support from Tess Weber ’21, presented “Is there evidence that students cheated when Arcadia’s math placement test went online?” Due to the pandemic, last summer the first-year math placement test was administered online, unmonitored, with no requirement that students leave their cameras on, a stark contrast to the strict in-person proctored conditions. The students employed several statistical techniques, including ANCOVA, to investigate whether these changes led to a different distribution of scores. The findings were reported and discussed using free statistical analysis programs JASP and Jamovi.
Madison Kuduk ’21 presented “Modeling gene expression using differential equations.” Gene expression is the process by which the information stored in DNA is converted into a functional gene product, such as protein. In simple cells, this process can be represented as a system of first-order differential equations that expresses the rate of change of mRNA and proteins. This model can provide insight into the interrelation of transcription and translation, the fundamental functions in gene expression, and act as a starting point toward a more advanced model for higher-order cells.
Hao Huang ’21, Youyuan Kong ’21, Jacob Walsh ’21, Zixue Wang ’21, and Shengxi Zhang ’21 presented “Parametric Insurance Product Design.” This report presented a design of a parametric insurance product for individual consumers in two neighboring countries, Ambernϊa and Palȍmϊnϊa. Analysis conducted on given health data in the countries allowed for the students to project losses and ultimately set premiums and triggering payouts for different genders, age groups, and risk factors. Comprehensive strategies were also provided for marketing and risk mitigation.
Zian Liu ’21, Qi Miao ’21, Yannan Niu ’22, and Xincheng Zhu ’21 presented “Health Index-Based Insurance Design for NEW WORLD.” The team designed a novel health insurance product by constructing a real-time health surveillance system for insurers in which they can assess a policyholder’s latest health status and make a quick payout if a certain condition has been met, regardless of the actual spending. Through analyzing a CDC survey data set related to behavioral risks, the students trained a multinomial logistic regression model. Using the health condition classifications from the model, they made further pricing strategies and financial projections for their client NEW WORLD.