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Description
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
Description
This paper attempts to introduce analytics and regression techniques into the National Hockey League. Hockey as a sport has been a slow adapter of analytics, and this can be attributed to poor data collection methods. Using data collected for hockeyreference.com, and R statistical software, the number of wins a team

This paper attempts to introduce analytics and regression techniques into the National Hockey League. Hockey as a sport has been a slow adapter of analytics, and this can be attributed to poor data collection methods. Using data collected for hockeyreference.com, and R statistical software, the number of wins a team experiences will be predicted using Goals For and Goals Against statistics from 2005-2017. The model showed statistical significance and strong normality throughout the data. The number of wins each team was expected to experience in 2016-2017 was predicted using the model and then compared to the actual number of games each team won. To further analyze the validity of the model, the expected playoff outcome for 2016-2017 was compared to the observed playoff outcome. The discussion focused on team's that did not fit the model or traditional analytics and expected forecasts. The possible discrepancies were analyzed using the Las Vegas Golden Knights as a case study. Possible next steps for data analysis are presented and the role of future technology and innovation in hockey analytics is discussed and predicted.
ContributorsVermeer, Brandon Elliot (Author) / Goegan, Brian (Thesis director) / Eaton, John (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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Description
A global trend towards cashlessness following the increase in technological advances in financial transactions lends way to a discussion of its various impacts on society. As part of this discussion, it is important to consider how this trend influences crime rates. The purpose of this project is to specifically investigate

A global trend towards cashlessness following the increase in technological advances in financial transactions lends way to a discussion of its various impacts on society. As part of this discussion, it is important to consider how this trend influences crime rates. The purpose of this project is to specifically investigate the relationship between a cashless society and the robbery rate. Using data collected from the World Bank’s Global Financial Inclusions Index and the United Nations Office of Drugs and Crime, we implemented a multilinear regression to observe this relationship across countries (n = 29). We aimed to do this by regressing the robbery rate on cashlessness and controlling for other related variables, such as gross domestic product and corruption. We found that as a country becomes more cashless, the robbery rate decreases (β = -677.8379, p = 0.071), thus providing an incentive for countries to join this global trend. We also conducted tests for heteroscedasticity and multicollinearity. Overall, our results indicate that a reduction in the amount of cash circulating within a country negatively impacts robbery rates.
ContributorsChoksi, Aashini S (Co-author) / Elliott, Keeley (Co-author) / Goegan, Brian (Thesis director) / McDaniel, Cara (Committee member) / School of International Letters and Cultures (Contributor) / Department of Economics (Contributor) / Dean, W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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Description
This study examines the economic impact of the opioid crisis in the United States. Primarily testing the years 2007-2018, I gathered data from the Census Bureau, Centers for Disease Control, and Kaiser Family Foundation in order to examine the relative impact of a one dollar increase in GDP per Capita

This study examines the economic impact of the opioid crisis in the United States. Primarily testing the years 2007-2018, I gathered data from the Census Bureau, Centers for Disease Control, and Kaiser Family Foundation in order to examine the relative impact of a one dollar increase in GDP per Capita on the death rates caused by opioids. By implementing a fixed-effects panel data design, I regressed deaths on GDP per Capita while holding the following constant: population, U.S. retail opioid prescriptions per 100 people, annual average unemployment rate, percent of the population that is Caucasian, and percent of the population that is male. I found that GDP per Capita and opioid related deaths are negatively correlated, meaning that with every additional person dying from opioids, GDP per capita decreases. The finding of this research is important because opioid overdose is harmful to society, as U.S. life expectancy is consistently dropping as opioid death rates rise. Increasing awareness on this topic can help prevent misuse and the overall reduction in opioid related deaths.
ContributorsRavi, Ritika Lisa (Author) / Goegan, Brian (Thesis director) / Hill, John (Committee member) / Department of Economics (Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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Description

Abstract
Objective: To assess the attitudes and knowledge of behavioral health technicians (BHTs)
towards opioid overdose management and to assess the effect of online training on opioid
overdose response on BHTs’ attitudes and knowledge, and the confidence to identify and
respond to opioid overdose situations.

Design/Methods: Pre-intervention Opioid Overdose Knowledge Scale (OOKS) and Opioid
Overdose Attitude

Abstract
Objective: To assess the attitudes and knowledge of behavioral health technicians (BHTs)
towards opioid overdose management and to assess the effect of online training on opioid
overdose response on BHTs’ attitudes and knowledge, and the confidence to identify and
respond to opioid overdose situations.

Design/Methods: Pre-intervention Opioid Overdose Knowledge Scale (OOKS) and Opioid
Overdose Attitude Scale (OOAS) surveys were administered electronically to five BHTs in
2020. Data obtained were de-identified. Comparisons between responses to pre-and post-surveys questions were carried out using the standardized Wilcoxon signed-rank statistical test(z). This study was conducted in a residential treatment center (RTC) with the institutional review board's approval from Arizona State University. BHTs aged 18 years and above, working at this RTC were included in the study.

Interventions: An online training was provided on opioid overdose response (OOR) and
naloxone administration and on when to refer patients with opioid use disorder (OUD) for
medication-assisted treatment.

Results: Compared to the pre-intervention surveys, the BHTs showed significant improvements
in attitudes on the overall score on the OOAS (mean= 26.4 ± 13.1; 95% CI = 10.1 - 42.7; z =
2.02; p = 0.043) and significant improvement in knowledge on the OOKS (mean= 10.6 ± 6.5;
95% CI = 2.5 – 18.7; z =2.02, p = 0.043).

Conclusions and Relevance: Training BHTs working in an RTC on opioid overdose response is
effective in increasing attitudes and knowledge related to opioid overdose management. opioid
overdose reversal in RTCs.

Keywords: Naloxone, opioid overdose, overdose education, overdose response program

ContributorsQuie, Georgette (Author) / Guthery, Ann (Thesis advisor)
Created2021-04-12
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Description
This paper aims to get a snapshot of charter school and public school performance in the state of California, specifically looking at high schools. Based off of data gathered on specific variables of interest and carefully constructed regression models, we are testing whether charter schools perform differently from public schools.

This paper aims to get a snapshot of charter school and public school performance in the state of California, specifically looking at high schools. Based off of data gathered on specific variables of interest and carefully constructed regression models, we are testing whether charter schools perform differently from public schools. This paper attempts to analyze results from standard OLS regression models and random effects GLS models, both with and without
interaction effects between charter schools and ethnicity and geographic area. While discussing results, this paper will also acknowledge limitations while drawing the line between correlation and causality. Our variable of interest throughout the paper is charter school, controlling for other factors that might impact API scores such as geographic area, demographics, and school
characteristics.
ContributorsValdez, Logan Taylor (Author) / Goegan, Brian (Thesis director) / Murphy, Alvin (Committee member) / Department of Information Systems (Contributor) / Dean, W.P. Carey School of Business (Contributor) / Department of Economics (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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Description
Objective: To assess the attitudes and knowledge of behavioral health technicians (BHTs) towards opioid overdose management and to assess the effect of online training on opioid overdose response on BHTs’ attitudes and knowledge, and the confidence to identify and respond to opioid overdose situations. Design/Methods: Pre-intervention Opioid Overdose Knowledge Scale (OOKS) and Opioid Overdose Attitude

Objective: To assess the attitudes and knowledge of behavioral health technicians (BHTs) towards opioid overdose management and to assess the effect of online training on opioid overdose response on BHTs’ attitudes and knowledge, and the confidence to identify and respond to opioid overdose situations. Design/Methods: Pre-intervention Opioid Overdose Knowledge Scale (OOKS) and Opioid Overdose Attitude Scale (OOAS) surveys were administered electronically to five BHTs in 2020. Data obtained were de-identified. Comparisons between responses to pre-and post-surveys questions were carried out using the standardized Wilcoxon signed-rank statistical test(z). This study was conducted in a residential treatment center (RTC) with the institutional review board's approval from Arizona State University. BHTs aged 18 years and above, working at this RTC were included in the study. Interventions: An online training was provided on opioid overdose response (OOR) and naloxone administration and on when to refer patients with opioid use disorder (OUD) for medication-assisted treatment. Results: Compared to the pre-intervention surveys, the BHTs showed significant improvements in attitudes on the overall score on the OOAS (mean= 26.4 ± 13.1; 95% CI = 10.1 - 42.7; z = 2.02; p = 0.043) and significant improvement in knowledge on the OOKS (mean= 10.6 ± 6.5; 95% CI = 2.5 – 18.7; z =2.02, p = 0.043). Conclusions and Relevance: Training BHTs working in an RTC on opioid overdose response is effective in increasing attitudes and knowledge related to opioid overdose management. opioid overdose reversal in RTCs.
Created2021-04-12