My project goes over creating a probability model to accurately predict the probability of a shot in the NHL becoming a goal. It explores different types of models to produce the most accurate model. The study explains which variables contribute most to whether a shot results in a goal or not and of those variables how teams can control them to have the most success.

The objective of my honors thesis was to implement the mindfulness habit of journaling over the course of six months, then use the journal entries as a means to reflect upon observations of pre-selected metrics (connecting Zen teachings to my daily life, accessing my ability to rest, navigating relationships to others, and developing compassion for myself) in order to track how learning about Zen Buddhist philosophy impacts my life.

This paper recommends amendments to the Montessori teaching system, which can in turn be adapted by individual educators or administrative school boards. The proposed tools mentioned in this paper follow the tenets of Constructivist teaching, which Montessori uses as some of its core teaching values (“Who and What is Montessori?”). Constructivist teaching argues that students learn best when they are able to apply their knowledge base to new learning experiences. The word comes from the idea that students are “constructing” their knowledge base one piece at a time, a process that starts from the ground, or base layer, and builds up from that. This construction involves physical representations of concepts, or guided experiences. Contrary to traditional, “top down” teaching, students learning through constructivist teaching get to experiment with learning concepts before a teacher explains the proper theory. These teachings try to generate excitement for the subject matter as extensions of students’ prior learning. Simulation and data visualization are powerful tools that allow students to discover the patterns present in natural processes by giving them the power to affect the environment and see the results. Implementation of the learning strategies of data visualizations and simulations should improve student performance and excitement in Earth and Space Science (ESS), while also being compliant with the Montessori teaching method.

Water markets are a promising method for adapting to water scarcity in the western United States, and the Colorado-Big Thompson Project (CBT) market is often held up as a prime example of their potential. While much has been written about the CBT market, the current academic literature tends to eschew structural modeling of supply and demand in favor of fitting hedonic price equations, which ignore many of the market’s unique characteristics. This paper proposes a model of supply and demand for CBT water which accounts for these unique features, including transaction supply, municipality stockpiling, and differences in behavior across different types of water users. The estimation of this model is made possible by novel administrative records data on both transfers and ownership of CBT water, the processing and features of which are described in detail. While the voluminous and messy nature of the data has prevented complete estimation of the model at this point, some preliminary results are presented along with a plan for future work.

In this project we focus on COVID-19 in a university setting. Arizona State University has a very large population on the Tempe Campus. With the emergence of diseases such as COVID-19, it is very important to track how such a disease spreads within that type of community. This is vital for containment measures and the safety of everyone involved. We found in the literature several epidemiology models that utilize differential equations for tracking a spread of a disease. However, our goal is to provide a granular look at how disease may spread through contact in a classroom. This thesis models a single ASU classroom and tracks the spread of a disease. It is important to note that our variables and declarations are not aligned with COVID-19 or any other specific disease but are chosen to exemplify the impact of some key parameters on the epidemic size. We found that a smaller transmissibility alongside a more spread-out classroom of agents resulted in fewer infections overall. There are many extensions to this model that are needed in order to take what we have demonstrated and align those ideas with COVID-19 and it’s spread at ASU. However, this model successfully demonstrates a spread of disease through single-classroom interaction, which is the key component for any university campus disease transmission model.