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How Blockchain Solutions Enable Better Decision Making Through Blockchain Analytics, Sammy Ter Haar 2022 University of Arkansas, Fayetteville

How Blockchain Solutions Enable Better Decision Making Through Blockchain Analytics, Sammy Ter Haar

Information Systems Undergraduate Honors Theses

Since the founding of computers, data scientists have been able to engineer devices that increase individuals’ opportunities to communicate with each other. In the 1990s, the internet took over with many people not understanding its utility. Flash forward 30 years, and we cannot live without our connection to the internet. The internet of information is what we called early adopters with individuals posting blogs for others to read, this was known as Web 1.0. As we progress, platforms became social allowing individuals in different areas to communicate and engage with each other, this was known as Web 2.0 ...


Attempting To Predict The Unpredictable: March Madness, Coleton Kanzmeier 2022 University of Nebraska at Omaha

Attempting To Predict The Unpredictable: March Madness, Coleton Kanzmeier

Theses/Capstones/Creative Projects

Each year, millions upon millions of individuals fill out at least one if not hundreds of March Madness brackets. People test their luck every year, whether for fun, with friends or family, or to even win some money. Some people rely on their basketball knowledge whereas others know it is called March Madness for a reason and take a shot in the dark. Others have even tried using statistics to give them an edge. I intend to follow a similar approach, using statistics to my advantage. The end goal is to predict this year’s, 2022, March Madness bracket. To ...


White Noise Space Analysis And Multiplicative Change Of Measures, Daniel Alpay, Palle Jorgensen, Motke Porat 2022 Chapman University

White Noise Space Analysis And Multiplicative Change Of Measures, Daniel Alpay, Palle Jorgensen, Motke Porat

Mathematics, Physics, and Computer Science Faculty Articles and Research

In this paper, we display a family of Gaussian processes, with explicit formulas and transforms. This is presented with the use of duality tools in such a way that the corresponding path-space measures are mutually singular. We make use of a corresponding family of representations of the canonical commutation relations (CCR) in an infinite number of degrees of freedom. A key feature of our construction is explicit formulas for associated transforms; these are infinite-dimensional analogs of Fourier transforms. Our framework is that of Gaussian Hilbert spaces, reproducing kernel Hilbert spaces and Fock spaces. The latter forms the setting for our ...


Testing Aftershock Forecasts Using Bayesian Methods, Elisa Dong 2022 The University of Western Ontario

Testing Aftershock Forecasts Using Bayesian Methods, Elisa Dong

Electronic Thesis and Dissertation Repository

The presence of strong aftershocks can increase the seismic hazard following a large earthquake and should be considered for operational earthquake forecasting and risk management. Aftershock forecasts are generated from seismicity models during the evolution of the aftershock sequence. This work compares quantitative test results of the forecasting abilities for three competing aftershock rate models - the modified Omori law, the Epidemic Type Aftershock Sequence model, and the compound Omori law - to identify the best performing model for forecasting the largest aftershock during the early aftershock sequence. Forecasts of large aftershock probabilities are generated by either the Extreme Value distribution or ...


A Survey On The Use Of Plastic Versus Biodegradable Bottles For Drinking Water Packaging In The United Arab Emirates, Himadri Rajput, Munjed A. Maraqa, Fatima Zraydi, Lina A. Al Khatib, Noor Ameen, Rime Ben ElKaid, Safia S. Al Jaberi, Noura A. Alharbi, Reka Howard, Ashraf Aly Hassan 2022 United Arab Emirates University

A Survey On The Use Of Plastic Versus Biodegradable Bottles For Drinking Water Packaging In The United Arab Emirates, Himadri Rajput, Munjed A. Maraqa, Fatima Zraydi, Lina A. Al Khatib, Noor Ameen, Rime Ben Elkaid, Safia S. Al Jaberi, Noura A. Alharbi, Reka Howard, Ashraf Aly Hassan

Faculty Publications, Department of Statistics

Due to intensive utilization and extensive production, plastic waste is becoming a serious threat to the environment and human health. The situation is even worse in countries such as the United Arab Emirates (UAE), where single-use plastic water bottles add to the load of plastic pollution. The main objective of this survey was to assess the extent of bottled water utilization by the UAE residents and their awareness of the environmental concerns arising from single-use plastic bottles. The aim was also to evaluate their willingness to shift towards using biodegradable plastic bottles. This study involved the feedback of 2589 respondents ...


Seasonal Variation In Terrestrial Invertebrate Subsidies To Tropical Streams And Implications For The Feeding Ecology Of Hart’S Rivulus (Anablepsoides Hartii), David C. Owens, Thomas N. Heatherly, Kent M. Eskridge, Colden V. Baxter, Steven A. Thomas 2022 Georgia Southern University

Seasonal Variation In Terrestrial Invertebrate Subsidies To Tropical Streams And Implications For The Feeding Ecology Of Hart’S Rivulus (Anablepsoides Hartii), David C. Owens, Thomas N. Heatherly, Kent M. Eskridge, Colden V. Baxter, Steven A. Thomas

Faculty Publications, Department of Statistics

Terrestrial invertebrates are important subsidies to fish diets, though their seasonal dynamics and importance to tropical stream consumers are particularly understudied. In this year-round study of terrestrial invertebrate input to two Trinidadian headwater streams with different forest canopy densities, we sought to (a) measure the mass and composition of terrestrial inputs with fall-in traps to evaluate the influences of seasonality, canopy cover, and rainfall intensity, and; (b) compare terrestrial and benthic prey importance to Anablepsoides hartii(Hart’s Rivulus), the dominant invertivorous fish in these streams, by concurrently measuring benthic and drifting invertebrate standing stocks and the volume and composition ...


Examining The Credibility Of Story-Based Causal Methodologies, Megan E. Kauffmann 2022 University of Denver

Examining The Credibility Of Story-Based Causal Methodologies, Megan E. Kauffmann

Electronic Theses and Dissertations

The purpose of this study was to explore how evaluators justify using story-based methodologies when examining causality. The two primary research questions of the study included: 1) what arguments are made by evaluators to justify the credibility of story-based causal methodologies to evaluation stakeholders; and 2) from the perspective of evaluators, how do contextual factors influence whether story-based causal methodologies are perceived as credible by evaluation stakeholders? A case study was conducted to examine the cases of four evaluators who had experience implementing a story-based methodology in an evaluation. Data collection procedures included two interviews with each participant and a ...


Expanding The Network Evaluation Toolkit: Combining Social Network Analysis & Qualitative Comparative Analysis, Debbie Gowensmith 2022 University of Denver

Expanding The Network Evaluation Toolkit: Combining Social Network Analysis & Qualitative Comparative Analysis, Debbie Gowensmith

Electronic Theses and Dissertations

Collective action networks are complex systems of interrelated individuals or groups that come together for a common social change purpose (Ernstson, 2011). Researchers have used social network analysis (SNA) to examine the relationship structures and characteristics of collective action networks. However, determining whether collective action networking produces outcomes has been challenging because networks are complex, affected by context, and produce interdependent data. I addressed these challenges by pairing SNA with qualitative comparative analysis (QCA), a configurational comparative method. Using QCA, researchers can tease out which conditions are necessary or sufficient to produce an outcome. I analyzed a collective action network ...


Confidence Interval For The Mean Of A Beta Distribution, Sean Rangel 2021 Stephen F Austin State University

Confidence Interval For The Mean Of A Beta Distribution, Sean Rangel

Electronic Theses and Dissertations

Statistical inference for the mean of a beta distribution has become increasingly popular in various fields of academic research. In this study, we developed a novel statistical model from likelihood-based techniques to evaluate various confidence interval techniques for the mean of a beta distribution. Simulation studies will be implemented to compare the performance of the confidence intervals. In addition to the development and study involving confidence intervals, we will also apply the confidence intervals to real biological data that was gathered by the Department of Biology at Stephen F. Austin State University and provide recommendations on the best practice.


Incorporating Molecular Markers And Causal Structure Among Traits Using A Smith-Hazel Index And Structural Equation Models, Juan Valente Hidalgo-Contreras, Josafhat Salinas-Ruiz, Kent M. Eskridge, Stephen P. Baenziger 2021 College of Postgraduates in Agricultural Sciences

Incorporating Molecular Markers And Causal Structure Among Traits Using A Smith-Hazel Index And Structural Equation Models, Juan Valente Hidalgo-Contreras, Josafhat Salinas-Ruiz, Kent M. Eskridge, Stephen P. Baenziger

Faculty Publications, Department of Statistics

The goal in breeding programs is to choose candidates that produce offspring with the best phenotypes. In conventional selection, the best candidate is selected with high genotypic values (unobserved), in the assumption that this is related to the observed phenotypic values for several traits. Multi-trait selection indices are used to identify superior genotypes when a number of traits are to be considered simultaneously. Often, the causal relationship among the traits is well known. Structural equation models (SEM) have been used to describe the causal relationships among variables in many biological systems. We present a method for multi-trait genomic selection that ...


Novel Statistical Modeling Methods For Traffic Video Analysis, Hang Shi 2021 New Jersey Institute of Technology

Novel Statistical Modeling Methods For Traffic Video Analysis, Hang Shi

Dissertations

Video analysis is an active and rapidly expanding research area in computer vision and artificial intelligence due to its broad applications in modern society. Many methods have been proposed to analyze the videos, but many challenging factors remain untackled. In this dissertation, four statistical modeling methods are proposed to address some challenging traffic video analysis problems under adverse illumination and weather conditions.

First, a new foreground detection method is presented to detect the foreground objects in videos. A novel Global Foreground Modeling (GFM) method, which estimates a global probability density function for the foreground and applies the Bayes decision rule ...


Factors Influencing Student Outcomes In A Large, Online Simulation-Based Introductory Statistics Course, Ella M. Burnham 2021 University of Nebraska-Lincoln

Factors Influencing Student Outcomes In A Large, Online Simulation-Based Introductory Statistics Course, Ella M. Burnham

Dissertations and Theses in Statistics

The demand for statistical knowledge and skills is growing in many disciplines, so more students are enrolling in introductory statistics courses (Blair, Kirkman, & Maxwell, 2018). At the same time, institutions are seeking course delivery methods that allow for greater flexibility for students, especially following the onset of the COVID-19 pandemic; therefore, there is more interest in the development and delivery of online introductory statistics courses.

To address this, I collaboratively designed an online introductory statistics course which focuses on simulation-based inference for the University of Nebraska-Lincoln. The course design was informed by the Community of Inquiry framework (Garrison, Anderson, & Archer, 2000). The course is delivered asynchronously and has the capacity for high enrollment. Following the development of the course, I co-taught this course from Fall 2018 to Spring 2021 and recruited enrolled students to participate in my study. Participants granted research access to several components of their normal coursework and completed three surveys: Survey of Attitudes Toward Statistics (36-question version pre-test and post-test; Schau, 2003a, 2003b) and the Distance Education and Technological Advancements Survey (Joosten & Reddy, 2015).

The primary goal of this study was to understand factors that influence student outcomes in this course. An intervention was designed to support the community of inquiry within the course and was implemented during Fall 2019 and Fall 2020. Using Bayesian hierarchical models, there was no evidence of an effect of the intervention on student outcomes. However, there were a variety of other self-reported factors that were found to be associated with student outcomes. The secondary aim of the study was to understand whether students' attitudes toward statistics changed during the term; however, descriptive statistics suggest that students' attitudes did not change during the term.

To address some ...


Prediction Intervals: The Effects And Identification Of Sparse Regions For Nonparametric Regression Methods, Jackson Faires 2021 Stephen F. Austin State University

Prediction Intervals: The Effects And Identification Of Sparse Regions For Nonparametric Regression Methods, Jackson Faires

Electronic Theses and Dissertations

In this work, we provide an overview of different nonparametric methods for prediction interval estimation and investigate how well they perform when making predictions in sparse regions of the predictor space. This sparsity is an extension to the more common concept of extrapolation in linear regression settings. Using simulation studies, we show that coverage probabilities using prediction intervals from quantile k-nearest neighbors and quantile random forest can be biased to low or too high from the nominal level under various situations of sparsity. We also introduce a test that can be used to see if a new data point lies ...


Fully Bayesian Analysis Of Relevance Vector Machine Classification With Probit Link Function For Imbalanced Data Problem, Wenyang Wang, Dongchu Sun, Peng Shao, Haibo Kuang, Cong Sui 2021 Dalian Maritime University

Fully Bayesian Analysis Of Relevance Vector Machine Classification With Probit Link Function For Imbalanced Data Problem, Wenyang Wang, Dongchu Sun, Peng Shao, Haibo Kuang, Cong Sui

Faculty Publications, Department of Statistics

The original RVM classification model uses the logistic link function to build the likelihood function making the model hard to be conducted since the posterior of the weight parameter has no closed-form solution. This article proposes the probit link function approach instead of the logistic one for the likelihood function in the RVM classification model, namely PRVM (RVM with the probit link function). We show that the posterior of the weight parameter in PRVM follows the Multivariate Normal distribution and achieves a closed-form solution. A latent variable is needed in our algorithms to simplify the Bayesian computation greatly, and its ...


Application Of Randomness In Finance, Jose Sanchez, Daanial Ahmad, Satyanand Singh 2021 CUNY New York City College of Technology

Application Of Randomness In Finance, Jose Sanchez, Daanial Ahmad, Satyanand Singh

Publications and Research

Brownian Motion which is also considered to be a Wiener process and can be thought of as a random walk. In our project we had briefly discussed the fluctuations of financial indices and related it to Brownian Motion and the modeling of Stock prices.


Does Defense Actually Win Championships? Using Statistics To Examine One Of The Greatest Stereotypes In Sports, Thomas Burkett 2021 University of South Carolina - Columbia

Does Defense Actually Win Championships? Using Statistics To Examine One Of The Greatest Stereotypes In Sports, Thomas Burkett

Senior Theses

A common saying in sports is that “defense wins championships.” However, the past decade of play in the modern NBA has seen a rise and focus in offensive efficiency and 3-pointers. This thesis tests whether defense can truly predict a championship winning team in today’s NBA through two-sample hypothesis testing and multiple logistic regression models. The results found that both defensive and offensive statistics were significant predictors of championship teams, meaning that a balanced team, rather than one specialized in defense alone, is a more accurate predictor of championship success.


The Fundamental Limit Theorem Of Countable Markov Chains, Nathanael Gentry 2021 Liberty University

The Fundamental Limit Theorem Of Countable Markov Chains, Nathanael Gentry

Senior Honors Theses

In 1906, the Russian probabilist A.A. Markov proved that the independence of a sequence of random variables is not a necessary condition for a law of large numbers to exist on that sequence. Markov's sequences -- today known as Markov chains -- touch several deep results in dynamical systems theory and have found wide application in bibliometrics, linguistics, artificial intelligence, and statistical mechanics. After developing the appropriate background, we prove a modern formulation of the law of large numbers (fundamental theorem) for simple countable Markov chains and develop an elementary notion of ergodicity. Then, we apply these chain convergence results ...


Adventuring Into Complexity By Exploring Data: From Complicity To Sustainability, Tim Lutz 2021 West Chester University

Adventuring Into Complexity By Exploring Data: From Complicity To Sustainability, Tim Lutz

Northeast Journal of Complex Systems (NEJCS)

Problems of sustainability are typically represented by major present-day challenges such as climate change, biodiversity loss, and environmental and social injustice. Framed this way, sustainable lives and societies depend on finding solutions to each problem. From another perspective, there is only one problem behind them all, stated by Gregory Bateson as: “…the difference between how nature works and the way people think,” and complexity provides a way to define and approach this problem. I extend Edgar Morin’s conceptions of restricted and general complexity into pedagogy to address problems of simplicity and reductionist teaching. The proposed pedagogy is based on ...


Entropic Dynamics Of Networks, Felipe Xavier Costa, Pedro Pessoa 2021 Department of Physics, University at Albany, State University of New York

Entropic Dynamics Of Networks, Felipe Xavier Costa, Pedro Pessoa

Northeast Journal of Complex Systems (NEJCS)

Here we present the entropic dynamics formalism for networks. That is, a framework for the dynamics of graphs meant to represent a network derived from the principle of maximum entropy and the rate of transition is obtained taking into account the natural information geometry of probability distributions. We apply this framework to the Gibbs distribution of random graphs obtained with constraints on the node connectivity. The information geometry for this graph ensemble is calculated and the dynamical process is obtained as a diffusion equation. We compare the steady state of this dynamics to degree distributions found on real-world networks.


Sars-Cov-2 Pandemic Analytical Overview With Machine Learning Predictability, Anthony Tanaydin, Jingchen Liang, Daniel W. Engels 2021 Southern Methodist University

Sars-Cov-2 Pandemic Analytical Overview With Machine Learning Predictability, Anthony Tanaydin, Jingchen Liang, Daniel W. Engels

SMU Data Science Review

Understanding diagnostic tests and examining important features of novel coronavirus (COVID-19) infection are essential steps for controlling the current pandemic of 2020. In this paper, we study the relationship between clinical diagnosis and analytical features of patient blood panels from the US, Mexico, and Brazil. Our analysis confirms that among adults, the risk of severe illness from COVID-19 increases with pre-existing conditions such as diabetes and immunosuppression. Although more than eight months into pandemic, more data have become available to indicate that more young adults were getting infected. In addition, we expand on the definition of COVID-19 test and discuss ...


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