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The purpose of this thesis was to develop a tool to provide information and data for design teams to use throughout the mobile application design process. Ideally, this would enable teams to see patterns in iterative design, and ultimately use data-driven analysis to make their own decisions. The initial problem

The purpose of this thesis was to develop a tool to provide information and data for design teams to use throughout the mobile application design process. Ideally, this would enable teams to see patterns in iterative design, and ultimately use data-driven analysis to make their own decisions. The initial problem was a lack of available information offered by mobile application design teams—the initial goal being to work closely with design teams to learn their decision-making methodology. However, every team that was reached out to responded with rejection, presenting a new problem: a lack of access to quality information regarding the decision-making process for mobile applications. This problem was addressed by the development of an ethical hacking script that retrieves reviews in bulk from the Google Play Store using Python. The project was a success—by feeding an application’s unique Play Store ID, the script retrieves a user-specified amount of reviews (up to millions) for that mobile application and the 4 “recommended” applications from the Play Store. Ultimately, this thesis proved that protected reviews on the Play Store can be ethically retrieved and used for data-driven decision making and identifying patterns in an application’s iterative design. This script provides an automated tool for teams to “put a finger on the pulse” of their target applications.
ContributorsDyer, Mitchell Patrick (Author) / Lin, Elva (Thesis director) / Giles, Charles (Committee member) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
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How prepared are individuals to work in an environment with sensitive information? Do business students believe a data security course would be a valuable addition to their curriculum? This study investigates W.P. Carey's role in preparing its students for jobs in which they most likely will have to handle large

How prepared are individuals to work in an environment with sensitive information? Do business students believe a data security course would be a valuable addition to their curriculum? This study investigates W.P. Carey's role in preparing its students for jobs in which they most likely will have to handle large amounts of important data. Roughly 500 students across varying majors and years of education in the W.P. Carey School of Business answered an assortment of questions on their computer habits, and responded to various scenarios to test their knowledge. The survey targeted three specific areas (Software Updates, Password Protection, and Phishing) which was believed to be most pertinent to the students' future roles as professionals. While a large number of those surveyed (roughly 65%) responded well to most questions, nearly a third of all the responses received indicated cause for concern or an indication of a lack of knowledge. It was suggested (and many respondents agreed) that further education be provided to students for their own well-being in addition to the wellbeing of their future employers.
ContributorsVaughan, Nathaniel D (Author) / Lin, Elva (Thesis director) / Doupé, Adam (Committee member) / School of Accountancy (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
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In this study, I sought to determine which NFL Combine metrics are predictive of future NFL success among the quarterback, running back, and wide receiver positions, with the hope of providing meaningful information that can be utilized by NFL executives when making decisions about draft selections. I gathered samples spanning

In this study, I sought to determine which NFL Combine metrics are predictive of future NFL success among the quarterback, running back, and wide receiver positions, with the hope of providing meaningful information that can be utilized by NFL executives when making decisions about draft selections. I gathered samples spanning across the years 2010-2015 of all three of the aforementioned position groups. Among these samples, I used certain criteria which split them up within their position groups. The two groups of players were identified as: those who had successful careers and those who had unsuccessful careers. Given this information, I performed t-tests and ANOVA between successful and unsuccessful groups with the goal of identifying which combine metrics are predictive of future NFL success, and which are not. For quarterbacks, the 40-yard dash, broad jump, three-cone, and 10-yard shuttle all appear to be predictive of success. Notably, quarterback height does not appear to be predictive, despite the popular belief that a quarterback should be tall if they are to succeed. For running backs, player weight, 40-yard dash, and three-cone all appear to be predictive of success, with the broad jump and 10-yard shuttle seemingly predicting success as well, albeit to a lesser degree of strength. For wide receivers, all metrics do not appear to be predictive of success, with the exception of the 40-yard dash, which only appears to be slightly predictive. While there are likely many other factors that contribute to a player’s success than tests administered at the NFL combine, NFL general managers can look to these results when making draft selections.

ContributorsFox, Dallas Alexander (Author) / Cox, Richard (Thesis director) / Lin, Elva (Committee member) / Dean, W.P. Carey School of Business (Contributor) / Sandra Day O'Connor College of Law (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05