Matching Items (7)
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- Creators: Computer Science and Engineering Program
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
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 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
Cryptocurrencies have become one of the most fascinating forms of currency and economics due to their fluctuating values and lack of centralization. This project attempts to use machine learning methods to effectively model in-sample data for Bitcoin and Ethereum using rule induction methods. The dataset is cleaned by removing entries with missing data. The new column is created to measure price difference to create a more accurate analysis on the change in price. Eight relevant variables are selected using cross validation: the total number of bitcoins, the total size of the blockchains, the hash rate, mining difficulty, revenue from mining, transaction fees, the cost of transactions and the estimated transaction volume. The in-sample data is modeled using a simple tree fit, first with one variable and then with eight. Using all eight variables, the in-sample model and data have a correlation of 0.6822657. The in-sample model is improved by first applying bootstrap aggregation (also known as bagging) to fit 400 decision trees to the in-sample data using one variable. Then the random forests technique is applied to the data using all eight variables. This results in a correlation between the model and data of 9.9443413. The random forests technique is then applied to an Ethereum dataset, resulting in a correlation of 9.6904798. Finally, an out-of-sample model is created for Bitcoin and Ethereum using random forests, with a benchmark correlation of 0.03 for financial data. The correlation between the training model and the testing data for Bitcoin was 0.06957639, while for Ethereum the correlation was -0.171125. In conclusion, it is confirmed that cryptocurrencies can have accurate in-sample models by applying the random forests method to a dataset. However, out-of-sample modeling is more difficult, but in some cases better than typical forms of financial data. It should also be noted that cryptocurrency data has similar properties to other related financial datasets, realizing future potential for system modeling for cryptocurrency within the financial world.
ContributorsBrowning, Jacob Christian (Author) / Meuth, Ryan (Thesis director) / Jones, Donald (Committee member) / McCulloch, Robert (Committee member) / Computer Science and Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
This thesis concerns the adoption of health information technology in the medical sector, specifically electronic health records (EHRs). EHRs have been seen as a great benefit to the healthcare system and will improve the quality of patient care. The federal government, has seen the benefit EHRs can offer, has been advocating the use and adoption of EHR for nearly a decade now. They have created policies that guide medical providers on how to implement EHRs. However, this thesis concerns the attitudes medical providers in Phoenix have towards government implementation. By interviewing these individuals and cross-referencing their answers with the literature this thesis wants to discover the pitfalls of federal government policy toward EHR implementation and EHR implementation in general. What this thesis found was that there are pitfalls that the federal government has failed to address including loss of provider productivity, lack of interoperability, and workflow improvement. However, the providers do say there is still a place for government to be involved in the implementation of EHR.
ContributorsKaldawi, Nicholas Emad (Author) / Lewis, Paul (Thesis director) / Cortese, Denis (Committee member) / Jones, Ruth (Committee member) / Barrett, The Honors College (Contributor) / School of Politics and Global Studies (Contributor) / School of Human Evolution and Social Change (Contributor)
Created2013-05
Description
The area of real-time baseball statistics presents several challenges that can be addressed using mobile devices. In order to accurately record real-time statistics, it is necessary to present the user with a concise interface that can be used to quickly record the necessary data during in-game events. In this project, we use a mobile application to address this by separating out the required input into pre-game and in-game inputs. We also explore the use of a mobile application to leverage crowd sourcing techniques, which address the challenge of accuracy and precision in subjective real-time statistics.
ContributorsVan Egmond, Eric David (Author) / Tadayon-Navabi, Farideh (Thesis director) / Wilkerson, Kelly (Committee member) / Gorla, Mark (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2013-05
Description
This project tackles a real-world example of a classroom with college students to discover what factors affect a student’s outcome in the class as well as investigate when and why a student who started well in the semester may end poorly later on. First, this project performs a statistical analysis to ensure that the total score of a student is truly based on the factors given in the dataset instead of due to random chance. Next, factors that are the most significant in affecting the outcome of scores in zyBook assignments are discovered. Thirdly, visualization of how students perform over time is displayed for the student body as a whole and students who started well at the beginning of the semester but trailed off towards the end. Lastly, the project also gives insight into the failure metrics for good starter students who unfortunately did not perform as well later in the course.
ContributorsChung, Michael (Author) / Meuth, Ryan (Thesis director) / Samara, Marko (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Computer Science and Engineering Program (Contributor)
Created2023-05
Description
This review explores popular gambling strategies often believed to guarantee wins, such as card counting and taking advantage of arbitrage. We present a mathematical overview of these systems to evaluate their theoretical effectiveness in ideal conditions by presenting prior research and mathematical proofs. This paper then generates results from these models using Monte Carlo simulations and compares them to data from real-world scenarios. Additionally, we examine reasons that might explain the discrepancies between theoretical and real-world results, such as the potential for dealers to detect and counteract card counting. Ultimately, although these strategies may fare well in theoretical scenarios, they struggle to create long-term winning solutions in casino or online gambling settings.
ContributorsBoyilla, Harsha (Author) / Clough, Michael (Thesis director) / Eikenberry, Steffen (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2024-05
Description
The process of cooking a turkey is a yearly task that families undertake in order to deliver a delicious centerpiece to a Thanksgiving meal. While other dishes accompany and comprise the traditional Thanksgiving supper, focusing on creating a turkey that satisfies the tastes of all guests is difficult, as preferences vary. Over the years, many cooking methods and preparation variations have come to light. This thesis studies these cooking methods and preparation variations, as well as the effects on the crispiness of the skin, the juiciness of the meat, the tenderness of the meat, and the overall taste, to simplify the choices that home cooks have to prepare a turkey that best fits their tastes. Testing and evaluation reveal that among deep-frying, grilling, and oven roasting turkey, a number of preparation variations show statistically significant changes relative to a lack of these preparation variations. For crispiness, fried turkeys are statistically superior, scoring about 1.5 points higher than other cooking methods on a 5 point scale. For juiciness, the best preparation variation was using an oven bag, with the oven roasted turkey scoring about 4.5 points on a 5 point scale. For tenderness, multiple methods are excellent, with the best three preparation variations in order being spatchcocking, brining, and using an oven bag, each of these preparation variations are just under a 4 out of 5. Finally, testing reaffirms that judges tend to have different subjective tastes, with some having different perceptions and opinions on some criteria, while statistically agreeing on others: there was 67% agreement among judges on crispiness and tenderness, while there was only 17% agreement on juiciness. Evaluation of these cooking methods, as well as their respective preparation variations, addresses the question of which methods are worthwhile endeavors for cooks.
ContributorsVance, Jarod (Co-author) / Lacsa, Jeremy (Co-author) / Green, Matthew (Thesis director) / Taylor, David (Committee member) / Chemical Engineering Program (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05