Interpreting an interaction in two-way ANOVA is fairly straightforward. However, in a study I conducted analyzing the impact of an environmental toxicant on fruit fly larvae, I had three independent variables and encountered a significant three-way interaction. This talk focuses on my investigation to understand the meaning of this interaction.

My analysis of data from a real-world experiment examining the impact of BPA exposure on fruit-fly larvae involved both parametric and non-parametric one-way ANOVA followed by appropriate post-hoc tests. I will discuss these statistical methods in the context of my data.

Three common techniques for analyzing pretest-post-test designs involving one control and one treatment group are: t-test comparing posttest scores only, t-test comparing gain scores, and analysis of covariance. In this talk we give the results of our R-based simulations, which indicate that the relative power of the techniques is a function of the pretest/posttest correlation coefficient.

For years, Arcadia’s math department has used its own test to place incoming students into the appropriate math classes. However, ours was the first effort to collect and analyze data to see if the test is doing a good job. Our talk focuses on the results of this analysis.

I will explore the concept of the number derivative (or the prime factorization of an integer) and primarily focus on its derivation modulo n. Through proving how to derive integers modulo powers of primes, we build toward an understanding of not only how to determine these number derivatives for any Zn, but also to count how many may exist on Zn.