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The NFL is one of largest and most influential industries in the world. In America there are few companies that have a stronger hold on the American culture and create such a phenomena from year to year. In this project aimed to develop a strategy that helps an NFL team

The NFL is one of largest and most influential industries in the world. In America there are few companies that have a stronger hold on the American culture and create such a phenomena from year to year. In this project aimed to develop a strategy that helps an NFL team be as successful as possible by defining which positions are most important to a team's success. Data from fifteen years of NFL games was collected and information on every player in the league was analyzed. First there needed to be a benchmark which describes a team as being average and then every player in the NFL must be compared to that average. Based on properties of linear regression using ordinary least squares this project aims to define such a model that shows each position's importance. Finally, once such a model had been established then the focus turned to the NFL draft in which the goal was to find a strategy of where each position needs to be drafted so that it is most likely to give the best payoff based on the results of the regression in part one.
ContributorsBalzer, Kevin Ryan (Author) / Goegan, Brian (Thesis director) / Dassanayake, Maduranga (Committee member) / Barrett, The Honors College (Contributor) / Economics Program in CLAS (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-05
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Over the past few decades, pharmaceutical spending has been increasing, due in large part to high prices of prescription drugs. In the United States, pharmaceutical manufacturers defend high prices by citing the high costs of research and development, which they argue spurns innovation and makes up for the high prices

Over the past few decades, pharmaceutical spending has been increasing, due in large part to high prices of prescription drugs. In the United States, pharmaceutical manufacturers defend high prices by citing the high costs of research and development, which they argue spurns innovation and makes up for the high prices paid by consumers. This study seeks to determine the validity of that claim and to fully understand the impact that R&D expenditures have on pharmaceutical drug prices. Employing a fixed effects regression, this study assesses the relationship between per capita R&D expenditure and per capita pharmaceutical spending (a stand-in variable for average drug price) for twelve OECD-member countries over a span of seven years. Holding country and year effects fixed, this regression shows a nearly one to one positive relationship between R&D expenditure and pharmaceutical spending, meaning a one-dollar increase in R&D expenditure increases pharmaceutical spending by around one-dollar as well. This impact, while statistically significant, is not that large, implying that R&D expenditures are not a strong driver of drug prices, contrary to what many pharmaceutical manufacturers argue.
ContributorsMartin, John Behun (Author) / Hill, Alexander (Thesis director) / Foster, William (Committee member) / Economics Program in CLAS (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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Description

This is a test plan document for Team Aegis' capstone project that has the goal of mitigating single event upsets in NAND flash memory caused by space radiation.

ContributorsForman, Oliver Ethan (Co-author) / Smith, Aiden (Co-author) / Salls, Demetra (Co-author) / Kozicki, Michael (Thesis director) / Hodge, Chris (Committee member) / Electrical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description

Radiation hardening of electronic devices is generally necessary when designing for the space environment. Non-volatile memory technologies are of particular concern when designing for the mitigation of radiation effects. Among other radiation effects, single-event upsets can create bit flips in non-volatile memories, leading to data corruption. In this paper, a

Radiation hardening of electronic devices is generally necessary when designing for the space environment. Non-volatile memory technologies are of particular concern when designing for the mitigation of radiation effects. Among other radiation effects, single-event upsets can create bit flips in non-volatile memories, leading to data corruption. In this paper, a Verilog implementation of a Reed-Solomon error-correcting code is considered for its ability to mitigate the effects of single-event upsets on non-volatile memories. This implementation is compared with the simpler procedure of using triple modular redundancy.

ContributorsSmith, Aidan W (Author) / Kozicki, Michael (Thesis director) / Hodge, Chris (Committee member) / Electrical Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description

In collaboration with Moog Broad Reach and Arizona State University, a<br/>team of five undergraduate students designed a hardware design solution for<br/>protecting flash memory data in a spaced-based radioactive environment. Team<br/>Aegis have been working on the research, design, and implementation of a<br/>Verilog- and Python-based error correction code using a Reed-Solomon method<br/>to

In collaboration with Moog Broad Reach and Arizona State University, a<br/>team of five undergraduate students designed a hardware design solution for<br/>protecting flash memory data in a spaced-based radioactive environment. Team<br/>Aegis have been working on the research, design, and implementation of a<br/>Verilog- and Python-based error correction code using a Reed-Solomon method<br/>to identify bit changes of error code. For an additional senior design project, a<br/>Python code was implemented that runs statistical analysis to identify whether<br/>the error correction code is more effective than a triple-redundancy check as well<br/>as determining if the presence of errors can be modeled by a regression model.

ContributorsSalls, Demetra Helen (Author) / Kozicki, Michael (Thesis director) / Hodge, Chris (Committee member) / Electrical Engineering Program (Contributor, Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
This paper seeks to highlight the strong correlation and potential causation between the presence of physical community bank branches in rural communities and local economic outcomes like payroll, employment, and establishments in a given region. To do this, I conduct a two-part analysis involving a fixed effects model with data

This paper seeks to highlight the strong correlation and potential causation between the presence of physical community bank branches in rural communities and local economic outcomes like payroll, employment, and establishments in a given region. To do this, I conduct a two-part analysis involving a fixed effects model with data from across the US and a regression discontinuity model of a subset of the data in parts of Delaware and Maryland. Overall, my results show a significant strong correlation between the number of bank branches in a region and the expected percent changes in economic outcomes, but I lack the results to claim causality between the opening or closure of a bank branch and changes in the local economy. This has relevance in understanding the need for physical bank branches as changes in the financial industry since the 2008 Financial Crisis, like online banking, have continued to accelerate.
ContributorsRodriguez, Luke (Author) / McDaniel, Cara (Thesis director) / Kuminoff, Nicolai (Committee member) / Barrett, The Honors College (Contributor) / School of Human Evolution & Social Change (Contributor) / School of International Letters and Cultures (Contributor) / Economics Program in CLAS (Contributor)
Created2022-12