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- Creators: Dean, W.P. Carey School of Business
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We attempted to apply a novel approach to stock market predictions. The Logistic Regression machine learning algorithm (Joseph Berkson) was applied to analyze news article headlines as represented by a bag-of-words (tri-gram and single-gram) representation in an attempt to predict the trends of stock prices based on the Dow Jones Industrial Average. The results showed that a tri-gram bag led to a 49% trend accuracy, a 1% increase when compared to the single-gram representation’s accuracy of 48%.
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During the global COVID-19 pandemic in 2020, many universities shifted their focus to hosting classes and events online for their student population in order to keep them engaged. The present study investigated whether an association exists between student engagement (an individual’s engagement with class and campus) and resilience. A single-shot survey was administered to 200 participants currently enrolled as undergraduate students at Arizona State University. A multiple regression analysis and Pearson correlations were calculated. A moderate, significant correlation was found between student engagement (total score) and resilience. A significant correlation was found between cognitive engagement (student’s approach and understanding of his learning) and resilience and between valuing and resilience. Contrary to expectations, participation was not associated with resilience. Potential explanations for these results were explored and practical applications for the university were discussed.
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sports, banking, and other disciplines. We use predictive analytics and modeling to
determine the impact of certain factors that increase the probability of a successful
fourth down conversion in the Power 5 conferences. The logistic regression models
predict the likelihood of going for fourth down with a 64% or more probability based on
2015-17 data obtained from ESPN’s college football API. Offense type though important
but non-measurable was incorporated as a random effect. We found that distance to go,
play type, field position, and week of the season were key leading covariates in
predictability. On average, our model performed as much as 14% better than coaches
in 2018.
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Collaborating with others is a crucial part of growing creatively, and gaining perspective. With different artistic mediums like dance, film, music and design, there is a lot artists can learn from one another. Art is also a way to convey important messages that reflect social, political and cultural issues, and artists have become increasingly responsible for presenting these issues in a way that will provoke thought and create change. “Luna” is a series of compositions with a goal of inviting the audience into a different world. The use of sound design and electronic music production paired with piano arrangements creates a vast, sonic landscape, and the titles of each piece are related to space. The live performance of the album also involves dance, which adds another human element to the experience.
The burden of dementia and its primary cause, Alzheimer’s disease, continue to devastate many with no available cure although present research has delivered methods for risk calculation and models of disease development that promote preventative strategies. Presently Alzheimer’s disease affects 1 in 9 people aged 65 and older amounting to a total annual healthcare cost in 2023 in the United States of $345 billion between Alzheimer’s disease and other dementias making dementia one of the costliest conditions to society (“2023 Alzheimer’s Disease Facts and Figures,” 2023). This substantial cost can be dramatically lowered in addition to a reduction in the overall burden of dementia through the help of risk prediction models, but there is still a need for models to deliver an individual’s predicted time of onset that supplements risk prediction in hopes of improving preventative care. The aim of this study is to develop a model used to predict the age of onset for all-cause dementias and Alzheimer’s disease using demographic, comorbidity, and genetic data from a cohort sample. This study creates multiple regression models with methods of ordinary least squares (OLS) and least absolute shrinkage and selection operator (LASSO) regression methods to understand the capacity of predictor variables that estimate age of onset for all-cause dementia and Alzheimer’s disease. This study is unique in its use of a diverse cohort containing 346 participants to create a predictive model that originates from the All of Us Research Program database and seeks to represent an accurate sampling of the United States population. The regression models generated had no predictive capacity for the age of onset but outline a simplified approach for integrating public health data into a predictive model. The results from the generated models suggest a need for continued research linking risk factors that estimate time of onset.
Out of all fifty states, Arizona boasts the greatest number of sunny days, which comes as no surprise to its residents. According to a CDC data report, Arizona has an average of nearly 286 total days of sun exposure. This sheer amount of sunlight could lead to the assumption that Arizona is also leading the way in harvesting this solar energy, but that isn’t the case. According to the S.E.I.A (Solar Energies Industries Association), Arizona is the fifth largest solar producer, while California comes in first by a significant lead. What happened in the history of California that caused this disparity in solar production that we see today and should Arizona follow in its footsteps? In this video essay, I consider the historical impact that climate change has had on California that directly led them to adopt environmental policies, such as wildfires, droughts, smog, and sea-level rise. These events threaten California specifically, due to its uniquely high population, geography, and climate, and they will continue to get worse as climate change subsists. Due to the persistent threat that they face, California was forced to pass environmental regulations that ultimately ended up developing them into a leader in environmental protectionism. Arizona, while also facing droughts, high heat, and poor air quality, has had its environmental progress greatly hindered by a lack of cohesive action at the State level. Based on information from the U.S Energy Information Agency, over the past 30 years, Arizona has been one of, if not the highest, carbon-dioxide emitters in the West. For a time there was some political response to this fact, but eventually, its momentum was halted in favor of economic challenges and continually stunted by mixed agendas, which polarized Arizona parties even more and left city governments to deal with climate change on their own. With solar being the cheapest means of clean energy production, it seems unavoidable that it will develop eventually. Solar becoming a topic of such polarization in Arizona makes it much more challenging, as it can only progress with bipartisan support, but climate change is inevitable so discourse has to be the first step towards meaningful change.
This thesis looks to explore the common barriers and perceptions surrounding sustainable living in westernized societies. We begin by understanding and explaining the complexity and importance of sustainability. Then we go on into a cultural comparison of sustainable lifestyles from places like Mongolia and Northern Arizona. After the comparison, we look deeper into mental barriers, perceptions, and influences that western minds have on the environment and how these beliefs affect their sustainable behaviors. After noticing these obstacles, we were able to research three key solutions to overcoming these barriers: daily practices, contextual motivation, and subjective values. Using these three solutions, this thesis builds out an implementation plan that allows you to help create a more sustainable lifestyle that you can start living out today.