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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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The concentration factor edge detection method was developed to compute the locations and values of jump discontinuities in a piecewise-analytic function from its first few Fourier series coecients. The method approximates the singular support of a piecewise smooth function using an altered Fourier conjugate partial sum. The accuracy and characteristic

The concentration factor edge detection method was developed to compute the locations and values of jump discontinuities in a piecewise-analytic function from its first few Fourier series coecients. The method approximates the singular support of a piecewise smooth function using an altered Fourier conjugate partial sum. The accuracy and characteristic features of the resulting jump function approximation depends on these lters, known as concentration factors. Recent research showed that that these concentration factors could be designed using aexible iterative framework, improving upon the overall accuracy and robustness of the method, especially in the case where some Fourier data are untrustworthy or altogether missing. Hypothesis testing methods were used to determine how well the original concentration factor method could locate edges using noisy Fourier data. This thesis combines the iterative design aspect of concentration factor design and hypothesis testing by presenting a new algorithm that incorporates multiple concentration factors into one statistical test, which proves more ective at determining jump discontinuities than the previous HT methods. This thesis also examines how the quantity and location of Fourier data act the accuracy of HT methods. Numerical examples are provided.
ContributorsLubold, Shane Michael (Author) / Gelb, Anne (Thesis director) / Cochran, Doug (Committee member) / Viswanathan, Aditya (Committee member) / Economics Program in CLAS (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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Description
Catastrophe events occur rather infrequently, but upon their occurrence, can lead to colossal losses for insurance companies. Due to their size and volatility, catastrophe losses are often treated separately from other insurance losses. In fact, many property and casualty insurance companies feature a department or team which focuses solely on

Catastrophe events occur rather infrequently, but upon their occurrence, can lead to colossal losses for insurance companies. Due to their size and volatility, catastrophe losses are often treated separately from other insurance losses. In fact, many property and casualty insurance companies feature a department or team which focuses solely on modeling catastrophes. Setting reserves for catastrophe losses is difficult due to their unpredictable and often long-tailed nature. Determining loss development factors (LDFs) to estimate the ultimate loss amounts for catastrophe events is one method for setting reserves. In an attempt to aid Company XYZ set more accurate reserves, the research conducted focuses on estimating LDFs for catastrophes which have already occurred and have been settled. Furthermore, the research describes the process used to build a linear model in R to estimate LDFs for Company XYZ's closed catastrophe claims from 2001 \u2014 2016. This linear model was used to predict a catastrophe's LDFs based on the age in weeks of the catastrophe during the first year. Back testing was also performed, as was the comparison between the estimated ultimate losses and actual losses. Future research consideration was proposed.
ContributorsSwoverland, Robert Bo (Author) / Milovanovic, Jelena (Thesis director) / Zicarelli, John (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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Description
One decision procedure dominates a given one if it performs well on the entire class of problems the given decision procedure performs well on, and then goes on to perform well on other problems that the given decision procedure does badly on. Performing well will be defined as generating higher

One decision procedure dominates a given one if it performs well on the entire class of problems the given decision procedure performs well on, and then goes on to perform well on other problems that the given decision procedure does badly on. Performing well will be defined as generating higher expected utility before entering a problem. In this paper it will be argued that the timeless decision procedure dominates the causal
and evidential decision procedures. It will also be argued in turn that the updateless decision procedure dominates the timeless decision procedure. The difficulties of formalizing a modern variant of the ”smoking gene” problem will then be briefly examined.
ContributorsHintze, Daniel Edward (Author) / Armendt, Brad (Thesis director) / Schlee, Edward (Committee member) / DeSerpa, Allan (Committee member) / Barrett, The Honors College (Contributor) / Economics Program in CLAS (Contributor)
Created2014-05
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Description
We seek a comprehensive measurement for the economic prosperity of persons with disabilities. We survey the current literature and identify the major economic indicators used to describe the socioeconomic standing of persons with disabilities. We then develop a methodology for constructing a statistically valid composite index of these indicators, and

We seek a comprehensive measurement for the economic prosperity of persons with disabilities. We survey the current literature and identify the major economic indicators used to describe the socioeconomic standing of persons with disabilities. We then develop a methodology for constructing a statistically valid composite index of these indicators, and build this index using data from the 2014 American Community Survey. Finally, we provide context for further use and development of the index and describe an example application of the index in practice.
ContributorsTheisen, Ryan (Co-author) / Helms, Tyler (Co-author) / Lewis, Paul (Thesis director) / Reiser, Mark (Committee member) / Economics Program in CLAS (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of Politics and Global Studies (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description

Career information for degrees in statistics and data science according to frequently asked questions and twelve major categories of interest: arts, business, education, engineering, environment, government, law, medicine, science, social science, sports, and technology.

ContributorsDerby-Lawson, Lili (Author) / Zheng, Yi (Thesis director) / Zhang, Helen (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of International Letters and Cultures (Contributor) / Economics Program in CLAS (Contributor) / School of Sustainability (Contributor)
Created2023-05
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Description
AARP estimates that 90% of seniors wish to remain in their homes during retirement. Seniors need assistance as they age, historically they have received assistance from either family members, nursing homes, or Continuing Care Retirement Communities. For seniors not wanting any of these options, there has been very few alternatives.

AARP estimates that 90% of seniors wish to remain in their homes during retirement. Seniors need assistance as they age, historically they have received assistance from either family members, nursing homes, or Continuing Care Retirement Communities. For seniors not wanting any of these options, there has been very few alternatives. Now, the emergence of the continuing care at home program is providing hope for a different method of elder care moving forward. CCaH programs offer services such as: skilled nursing care, care coordination, emergency response systems, aid with personal and health care, and transportation. Such services allow seniors to continue to live in their own home with assistance as their health deteriorates over time. Currently, only 30 CCaH programs exist. With the growth of the elderly population in the coming years, this model seems poised for growth.
ContributorsSturm, Brendan (Author) / Milovanovic, Jelena (Thesis director) / Hassett, Matthew (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Economics Program in CLAS (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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Description

This thesis proposes an extension of David Lewis's causal influence account of causation, providing a method to calculate the `degrees of causal influence.' By providing a quantitative approach to causal influence, I find that that the influence approach can assess statements that involve causal redundancies, allowing the assessor to attribute

This thesis proposes an extension of David Lewis's causal influence account of causation, providing a method to calculate the `degrees of causal influence.' By providing a quantitative approach to causal influence, I find that that the influence approach can assess statements that involve causal redundancies, allowing the assessor to attribute primary causal responsibility to the contending cause with a higher net influence value. The causal influence calculation also addresses criticisms towards Lewis's influence account, namely those involving `inert zones' of influence, the use of the term `might,' trumping versus symmetric overdetermination, and Lewis's clause requiring stepwise influence. This thesis also compares the results of causal influence in multiple toy cases including Two Rocks, both the asymmetric and symmetric variants, demonstrating that causal influence overcomes many of the core issues in Lewis's initial counterfactual account of causation. Using the asymmetric Two Rocks variant, this thesis also provides a detailed example of how to use the calculation and a discussion of the calculation's limitations. The main drawbacks of the quantitative method for causal influence seems to be the effort that it requires and issues in finding measurable qualities to compare the similarity/difference between possible worlds. Using the Two Rocks case, however, the causal influence calculation reaches the same conclusions as what Lewis suggests. A primary remaining issue is applying the calculation to instances of causation by omission, however this seems to only be a problem in using the equations rather than a problem within the idea of causal influence itself. Also, there may still be issues in justifying comparative overall similarity. However, this is an issue that both the counterfactual and influence accounts face.

ContributorsKha, Rachael Thuy-Trang (Author) / Watson, Jeffrey (Thesis director) / Botham, Thad (Committee member) / McElhoes, David (Committee member) / Historical, Philosophical & Religious Studies, Sch (Contributor) / Chemical Engineering Program (Contributor) / Economics Program in CLAS (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
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Description
A factor accounting for the COVID-19 pandemic was added to a generalized linear model to more accurately predict unpaid claims. COVID-19 has affected not just healthcare, but all sectors of the economy. Because of this, whether or not an automobile insurance claim is filed during the pandemic needs to be

A factor accounting for the COVID-19 pandemic was added to a generalized linear model to more accurately predict unpaid claims. COVID-19 has affected not just healthcare, but all sectors of the economy. Because of this, whether or not an automobile insurance claim is filed during the pandemic needs to be taken into account while estimating unpaid claims. Reserve-estimating functions such as glmReserve from the “ChainLadder” package in the statistical software R were experimented with to produce their own results. Because of their insufficiency, a manual approach to building the model turned out to be the most proficient method. Utilizing the GLM function, a model was built that emulated linear regression with a factor for COVID-19. The effects of such a model are analyzed based on effectiveness and interpretablility. A model such as this would prove useful for future calculations, especially as society is now returning to a “normal” state.
ContributorsKossler, Patrick (Author) / Zicarelli, John (Thesis director) / Milovanovic, Jelena (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2022-05
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Description

Four-dimensionalism is a popular philosophical view of how we persist through time. However, some philosophers, such as Mark Johnston and Eric Olson, argue that four-dimensionalism has perverse implications on our practical ethics. This is because, if four-dimensionalism is true, then there exist entities called personites. And if personites exist, then

Four-dimensionalism is a popular philosophical view of how we persist through time. However, some philosophers, such as Mark Johnston and Eric Olson, argue that four-dimensionalism has perverse implications on our practical ethics. This is because, if four-dimensionalism is true, then there exist entities called personites. And if personites exist, then many of the ordinary prudential, social, and moral habits we engage in, like present self-sacrifice for future benefit, promising to do something painful in the future, or being held responsible for something the we did in the past, subjects personites to suffering without sufficient compensation, consent, or desert. And this would be immoral according to our common-sense morality. In this paper, I argue that if four-dimensionalism is true, and personites exist, then we are still morally permitted to engage in the above practices. If four-dimensionalism turns out to be true, it has no perverse implications on how we ought to live.

ContributorsRavi, Ashwin (Author) / Portmore, Douglas (Thesis director) / Calhoun, Cheshire (Committee member) / Barrett, The Honors College (Contributor) / Economics Program in CLAS (Contributor) / Historical, Philosophical & Religious Studies, Sch (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2022-05