Matching Items (18)
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- All Subjects: Statistics
- Creators: Department of Information Systems
Description
This thesis was conducted to study and analyze the fund allocation process adopted by different states in the United States to reduce the impact of the Covid-19 virus. Seven different states and their funding methodologies were compared against the case count within the state. The study also focused on development of a physical distancing index based on three significant attributes. This index was then compared to the expenditure and case counts to support decision making.
A regression model was developed to analyze and compare how different states case counts played out against the regression model and the risk index.
ContributorsJaisinghani, Shaurya (Author) / Mirchandani, Pitu (Thesis director) / Clough, Michael (Committee member) / McCarville, Daniel R. (Committee member) / Industrial, Systems & Operations Engineering Prgm (Contributor) / Department of Information Systems (Contributor) / Industrial, Systems & Operations Engineering Prgm (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
League of Legends is a Multiplayer Online Battle Arena (MOBA) game. MOBA games are generally formatted where two teams of five, each player controlling a character (champion), will try to take each other's base as quickly as possible. Currently, with about 70 million, League of Legends is number one in the digital entertainment industry with $1.63 billion dollars of revenue in year 2015. This research analysis scopes in on the niche of the "Jungler" role between different tiers of player in League of Legends. I uncovered differences in player strategy that may explain the achievement of high rank using data aggregation through Riot Games' API, data slicing with time-sensitive data, random sampling, clustering by tiers, graphical techniques to display the cluster, distribution analysis and finally, a comprehensive factor analysis on the data's implications.
ContributorsPoon, Alex (Author) / Clark, Joseph (Thesis director) / Simon, Alan (Committee member) / Department of Information Systems (Contributor) / Department of Management (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
The object of the present study is to examine methods in which the company can optimize their costs on third-party suppliers whom oversee other third-party trade labor. The third parties in scope of this study are suspected to overstaff their workforce, thus overcharging the company. We will introduce a complex spreadsheet model that will propose a proper project staffing level based on key qualitative variables and statistics. Using the model outputs, the Thesis team proposes a headcount solution for the company and problem areas to focus on, going forward. All sources of information come from company proprietary and confidential documents.
ContributorsLoo, Andrew (Co-author) / Brennan, Michael (Co-author) / Sheiner, Alexander (Co-author) / Hertzel, Michael (Thesis director) / Simonson, Mark (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor) / Department of Finance (Contributor) / Department of Supply Chain Management (Contributor) / WPC Graduate Programs (Contributor) / School of Accountancy (Contributor)
Created2014-05
Description
In this research we consider stochastic models of Glioblastoma Multiforme brain tumors. We first look at a model by K. Swanson et al., which describes the dynamics as random diffusion plus deterministic logistic growth. We introduce a stochastic component in the logistic growth in the form of a random growth rate defined by a Poisson process. We show that this stochastic logistic growth model leads to a more accurate evaluation of the tumor growth compared its deterministic counterpart. We also discuss future plans to incorporate individual patient geometry, extend the model to three dimensions and to incorporate effects of different treatments into our model, in collaboration with a local hospital.
ContributorsManning, Michael Clare (Author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / Gardner, Carl (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of Letters and Sciences (Contributor) / School of Human Evolution and Social Change (Contributor)
Created2013-12
Description
Adaptive therapy utilizes competitive interactions between resistant and sensitive cells by keeping some sensitive cells to control tumor burden with the aim of increasing overall survival and time to progression. The use of adaptive therapy to treat breast cancer, ovarian cancer, and pancreatic cancer in preclinical models has shown significant results in controlling tumor growth. The purpose of this thesis is to draft a protocol to study adaptive therapy in a preclinical model of breast cancer on MCF7, estrogen receptor-positive, cells that have evolved resistance to fulvestrant and palbociclib (MCF7 R). In this study, we used two protocols: drug dose adjustment and intermittent therapy. The MCF7 R cell lines were injected into the mammary fat pads of 11-month-old NOD/SCID gamma (NSG) mice (18 mice) which were then treated with gemcitabine.<br/>The results of this experiment did not provide complete information because of the short-term treatments. In addition, we saw an increase in the tumor size of a few of the treated mice, which could be due to the metabolism of the drug at that age, or because of the difference in injection times. Therefore, these adaptive therapy protocols on hormone-refractory breast cancer cell lines will be repeated on young, 6-week old mice by injecting the cell lines at the same time for all mice, which helps the results to be more consistent and accurate.
ContributorsConti, Aviona (Author) / Maley, Carlo (Thesis director) / Blattman, Joseph (Committee member) / Seyedi, Sareh (Committee member) / School of Life Sciences (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Over the course of six months, we have worked in partnership with Arizona State University and a leading producer of semiconductor chips in the United States market (referred to as the "Company"), lending our skills in finance, statistics, model building, and external insight. We attempt to design models that help predict how much time it takes to implement a cost-saving project. These projects had previously been considered only on the merit of cost savings, but with an added dimension of time, we hope to forecast time according to a number of variables. With such a forecast, we can then apply it to an expense project prioritization model which relates time and cost savings together, compares many different projects simultaneously, and returns a series of present value calculations over different ranges of time. The goal is twofold: assist with an accurate prediction of a project's time to implementation, and provide a basis to compare different projects based on their present values, ultimately helping to reduce the Company's manufacturing costs and improve gross margins. We believe this approach, and the research found toward this goal, is most valuable for the Company. Two coaches from the Company have provided assistance and clarified our questions when necessary throughout our research. In this paper, we begin by defining the problem, setting an objective, and establishing a checklist to monitor our progress. Next, our attention shifts to the data: making observations, trimming the dataset, framing and scoping the variables to be used for the analysis portion of the paper. Before creating a hypothesis, we perform a preliminary statistical analysis of certain individual variables to enrich our variable selection process. After the hypothesis, we run multiple linear regressions with project duration as the dependent variable. After regression analysis and a test for robustness, we shift our focus to an intuitive model based on rules of thumb. We relate these models to an expense project prioritization tool developed using Microsoft Excel software. Our deliverables to the Company come in the form of (1) a rules of thumb intuitive model and (2) an expense project prioritization tool.
ContributorsAl-Assi, Hashim (Co-author) / Chiang, Robert (Co-author) / Liu, Andrew (Co-author) / Ludwick, David (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Michael (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor) / Department of Finance (Contributor) / Department of Economics (Contributor) / Department of Supply Chain Management (Contributor) / School of Accountancy (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Mechanical and Aerospace Engineering Program (Contributor) / WPC Graduate Programs (Contributor)
Created2015-05
Description
In baseball, a starting pitcher has historically been a more durable pitcher capable of lasting long into games without tiring. For the entire history of Major League Baseball, these pitchers have been expected to last 6 innings or more into a game before being replaced. However, with the advances in statistics and sabermetrics and their gradual acceptance by professional coaches, the role of the starting pitcher is beginning to change. Teams are experimenting with having starters being replaced quicker, challenging the traditional role of the starting pitcher. The goal of this study is to determine if there is an exact point at which a team would benefit from replacing a starting or relief pitcher with another pitcher using statistical analyses. We will use logistic stepwise regression to predict the likelihood of a team scoring a run if a substitution is made or not made given the current game situation.
ContributorsBuckley, Nicholas J (Author) / Samara, Marko (Thesis director) / Lanchier, Nicolas (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Exchange traded funds (ETFs) in many ways are similar to more traditional closed-end mutual funds, although thee differ in a crucial way. ETFs rely on a creation and redemption feature to achieve their functionality and this mechanism is designed to minimize the deviations that occur between the ETF’s listed price and the net asset value of the ETF’s underlying assets. However while this does cause ETF deviations to be generally lower than their mutual fund counterparts, as our paper explores this process does not eliminate these deviations completely. This article builds off an earlier paper by Engle and Sarkar (2006) that investigates these properties of premiums (discounts) of ETFs from their fair market value. And looks to see if these premia have changed in the last 10 years. Our paper then diverges from the original and takes a deeper look into the standard deviations of these premia specifically.
Our findings show that over 70% of an ETFs standard deviation of premia can be explained through a linear combination consisting of two variables: a categorical (Domestic[US], Developed, Emerging) and a discrete variable (time-difference from US). This paper also finds that more traditional metrics such as market cap, ETF price volatility, and even 3rd party market indicators such as the economic freedom index and investment freedom index are insignificant predictors of an ETFs standard deviation of premia when combined with the categorical variable. These findings differ somewhat from existing literature which indicate that these factors should have a significant impact on the predictive ability of an ETFs standard deviation of premia.
Our findings show that over 70% of an ETFs standard deviation of premia can be explained through a linear combination consisting of two variables: a categorical (Domestic[US], Developed, Emerging) and a discrete variable (time-difference from US). This paper also finds that more traditional metrics such as market cap, ETF price volatility, and even 3rd party market indicators such as the economic freedom index and investment freedom index are insignificant predictors of an ETFs standard deviation of premia when combined with the categorical variable. These findings differ somewhat from existing literature which indicate that these factors should have a significant impact on the predictive ability of an ETFs standard deviation of premia.
ContributorsZhang, Jingbo (Co-author, Co-author) / Henning, Thomas (Co-author) / Simonson, Mark (Thesis director) / Licon, L. Wendell (Committee member) / Department of Finance (Contributor) / Department of Information Systems (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
What is a “Good Economy”? Analysis of Economic Metrics & Their Political Impact on the United States
Description
The goal of this research paper is to analyze how we define economic success and how that affects large corporations and consumers. This paper asks the questions: What do we define as a good economy? What metrics are currently utilized? And how do perceptions of a good economy influence politics? Overall, the research seeks to identify common economic and financial fallacies held by the average citizen and offer alternative methods of how socio-economic information is presented to the consumers. Consumers play a major role in the market, and the information they receive has a considerable impact on their behaviors. Determining why the present economic analysis is used is the first step in finding ways to improve the system. Observing past political and economic trends and relating them to current issues is necessary for finding future solutions.
ContributorsTosca, Carlos (Author) / Brian, Jennifer (Thesis director) / Sadusky, Brian (Committee member) / Department of Information Systems (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
Over the past several decades, analytics have become more and more prevalent in the game of baseball. Statistics are used in nearly every facet of the game. Each team develops its own processes, hoping to gain a competitive advantage over the rest of the league. One area of the game that has struggled to produce definitive analytics is amateur scouting. This project seeks to resolve this problem through the creation of a new statistic, Valued Plate Appearance Index (VPI). The problem is identified through analysis that was performed to determine whether any correlation exists between performances at the country's top amateur baseball league, the Cape Cod League, and performances in Major League Baseball. After several stats were analyzed, almost no correlation was determined between the two. This essentially means that teams have no way to statistically analyze Cape Cod League performance and project future statistics. An inherent contextual error in these amateur statistics prevents them from correlating. The project seeks to close that contextual gap and create concrete, encompassing values to illustrate a player's offensive performance in the Cape League. To solve for this problem, data was collected from the 2017 CCBL season. In addition to VPI, Valued Plate Appearance Approach (VPA) and Valued Plate Appearance Result (VPR) were created to better depict a player's all-around performance in each plate appearance. VPA values the quality of a player's approach in each plate appearance. VPR values the quality of the contact result, excluding factors out of the hitter's control. This statistic isolates player performance as well as eliminates luck that cannot normally be taken into account. This paper results in the segmentation of players from the 2017 CCBL into four different groups, which project how they will perform as they transition into professional baseball. These groups and the creation of these statistics could be essential tools in the evaluation and projection of amateur players by Major League clubs for years to come.
ContributorsLothrop, Joseph Kent (Author) / Eaton, John (Thesis director) / McIntosh, Daniel (Committee member) / Department of Information Systems (Contributor) / Department of Marketing (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12