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Articles 1 - 30 of 136
Full-Text Articles in Other Statistics and Probability
A New Approach To Generate Combinatorial Patterns In Logical Analysis Of Data And Its Application To Predict College Retention, Salihah Ahmed E. Jaafari
A New Approach To Generate Combinatorial Patterns In Logical Analysis Of Data And Its Application To Predict College Retention, Salihah Ahmed E. Jaafari
Theses and Dissertations
Student retention and degree completion remain central challenges for higher-education institutions, with significant implications for student success, institutional effectiveness, and public accountability. While advances in predictive analytics have enabled earlier identification of students at risk of withdrawal, many commonly used machine learning approaches suffer from limited interpretability, constraining their practical usefulness for advising, intervention, and policy decision making. This dissertation addresses the problem of predicting student persistence by developing and evaluating optimization based, interpretable classification models within the Logical Analysis of Data (LAD) framework. Building on existing LAD formulations, this research introduces two novel pattern generation models, the Best Term …
Information Theory Analysis Of The Solar Wind Magnetic Structures For Space Weather Prediction, Katherine Holland
Information Theory Analysis Of The Solar Wind Magnetic Structures For Space Weather Prediction, Katherine Holland
Doctoral Dissertations and Master's Theses
Forecasting space weather at Earth is highly complicated, because of the limited measurements of the dynamic processes in the Sun that span multiple temporal, spatial, and energy-scales. The solar wind is a highly structured, multi-scale, evolving plasma and consists of coronal mass ejections (CMEs), stream interaction regions (SIRs), expanding flux tubes (Borovsky, 2008), and interplanetary magnetic field (IMF) discontinuities and fluctuations. The aim of this research is to improve our understanding of the evolution and dissipation of different scale-size solar wind magnetic structures as they move from the Sun-Earth Lagrange point 1 (L1) to Earth's bow shock and, ultimately, to …
Applications Of Machine Learning For Evaluating Downward-Coupled Stratosphere-Troposphere Interactions And Subseasonal Forecasts Of Opportunity, Elena M. Fernandez
Applications Of Machine Learning For Evaluating Downward-Coupled Stratosphere-Troposphere Interactions And Subseasonal Forecasts Of Opportunity, Elena M. Fernandez
Electronic Theses & Dissertations (2024 - present)
Wintertime stratospheric dynamics provide key information for understanding atmospheric teleconnections and improving subseasonal-to-seasonal (S2S) predictions on timescales of two weeks to two months. Periods of enhanced predictability, often referred to as forecasts of opportunity, arise from large-scale teleconnected variability, within which the stratosphere serves as an important precursor for tropospheric states, such as near-surface temperatures. While traditional diagnostics of downward coupled stratosphere-troposphere interactions typically rely on zonal-mean representations of wind and geopotential height, this dissertation presents an alternative vortex-centric framework through metrics that capture the daily geometric and dynamical evolution of the stratospheric polar vortex. The proposed stratospheric …
Learning Weibull Loss Severity Models From Truncated And Censored Data, Majed Alkhasha
Learning Weibull Loss Severity Models From Truncated And Censored Data, Majed Alkhasha
Graduate Studies Theses and Dissertations 2026
In modern actuarial science and risk management, due to various loss control mechanisms, observed severity losses are typically left-truncated at the deductible, right-censored at the policy limit, and scaled by a pre-specified co-insurance factor. This results in two types of actuarial payment random variables: payment-per-payment (PPP) and payment-per-loss (PPL). To learn ground-up Weibull loss severity models from PPP and PPL sample data, we implement two estimation techniques: Maximum Likelihood Estimation (MLE) and the dynamic Method of Trimmed Moments (MTM). MLE is employed to obtain efficient estimates of the Weibull shape and scale parameters. However, MLE may assign unnecessarily large point …
Human Capital, Immigration, And Growth: A State-Level Dynamic Panel Study, William R. Cooper
Human Capital, Immigration, And Growth: A State-Level Dynamic Panel Study, William R. Cooper
Graduate Theses and Dissertations (2019 - present)
This study examines whether who immigrates, rather than how many, matters for state economic growth in the United States. It integrates a policy-relevant proxy for skill (H-1B approvals) into an augmented Solow framework that separates immigration's quantity channel from its human capital channel and estimates dynamic effects in a balanced quarterly panel of 50 states (2010 to 2023 ). The empirical strategy estimates a two-step difference GMM Arellano-Bond model that reinforces identification using a double/debiased machine learning (DML) variant that orthogonalizes high-dimensional nuisance components via cross-fitting. This design targets the distinct roles of immigrant headcount versus skill in per capita …
Exploring The Impact Of Statistics Course Modality On Student Learning: A Mixed Methods Approach, Becky Kelleman
Exploring The Impact Of Statistics Course Modality On Student Learning: A Mixed Methods Approach, Becky Kelleman
Electronic Theses and Dissertations
The importance of statistical literacy has become increasingly evident, as individuals grapple with interpreting statistics to inform critical decisions. Despite the recognized significance of statistical literacy, challenges persist in both educators’ and students’ efforts to navigate the complexities of statistics education. The purpose of this study is to explore the impact of different course modalities on undergraduate students’ academic performance in introductory statistics courses. Using Social Cognitive Theory (SCT) as a theoretical framework, this research aims to shed light on the complex dynamics influencing statistical literacy attainment. By addressing gaps and inconsistencies in the current literature, this study seeks to …
Performance Of The Two Sample Likelihood Ratio Test Under A Nested Dirichlet: A Simulation Study, Edwina Agyeman
Performance Of The Two Sample Likelihood Ratio Test Under A Nested Dirichlet: A Simulation Study, Edwina Agyeman
Electronic Theses and Dissertations
Compositional data analysis (CoDA) addresses multivariate data constrained to a constant sum, such as proportions or percentages. Originating from early warnings regarding misinterpretation by Pearson (1897), the field was formalized by John Aitchison in 1986, whose foundational work remains highly influential. Over time, new modeling techniques and visualization tools have advanced the field, as noted by Greenacre et al. More recently, Turner et al. proposed an approach based on the Nested Dirichlet Distribution (NDD), which accommodates more flexible dependence structures than the standard Dirichlet model. This thesis builds on the methodology of Turner et al. Chapter 1 introduces the nature …
How’S It Growing? Tools For Observing Snow And Sea Ice In A Changing Arctic Ocean, Ian Alexander Raphael
How’S It Growing? Tools For Observing Snow And Sea Ice In A Changing Arctic Ocean, Ian Alexander Raphael
Dartmouth College Ph.D Dissertations
September Arctic sea ice extent has diminished by roughly 50% in the 45 years since satellite observations began. The Arctic Ocean may experience ice-free summers within the next decade, with implications for habitat, resource extraction, geopolitics, and local and global climate change. To predict how Arctic sea ice will change in the future, we need to understand its behavior in the present. In situ sea ice mass balance measurements (snow accumulation, ice growth, snow and ice surface melt, and bottom melt) are essential for studying the processes driving rapid changes in the ice pack, and for validating remote sensing measurements …
A Study On Fuzzy Time-Series And Its Applications To Stock Price Forecasting, Takeshi Stormer
A Study On Fuzzy Time-Series And Its Applications To Stock Price Forecasting, Takeshi Stormer
University Honors Theses
Fuzzy mathematics looks to incorporate the vagueness that exists within the real world, specifically regarding imprecise classes, or non-numerical information expressed as "linguistic" variables. Since most traditional mathematical theories do not have the ability to be applied with the exactness that is otherwise seen in mathematics. As such, there had been many applications of fuzzy mathematics throughout many different fields of mathematics, including that of forecasting. By exploring the fundamentals of fuzzy mathematics, including fuzzy sets, operations of fuzzy sets, the surface level introduction to fuzzy logic, fuzzy relations, operations of fuzzy relations, and fuzzy time-series, this work looks to …
Babies, Babes, And Bayes: Modeling Mother-Infant Feedings With Bayesian Multilevel Hidden Markov Models, Zachary G. Felix
Babies, Babes, And Bayes: Modeling Mother-Infant Feedings With Bayesian Multilevel Hidden Markov Models, Zachary G. Felix
Master's Theses
Understanding the interaction between mother and baby during feeding is critical for the long-term development health of the baby. Overfeeding can lead to later obesity, while underfeeding can lead to malnutrition. In a recent study, the behaviors exhibited by mother-infant dyads across multiple ages of infants have been observed and coded according to the Baby Behaviors when Satiated (BABES) coding scheme. However, creating models using the data obtained from this coding is no simple task since the data coding is continuous, multivariate, and longitudinal in nature. The specific model utilized for these data is a hidden Markov model, since there …
Clusters, Trends, And Choices: Feature Selection In Interactive Statistical Graphics, Dylan Le
Clusters, Trends, And Choices: Feature Selection In Interactive Statistical Graphics, Dylan Le
Master's Theses
Exploratory data analysis (EDA) is a method for uncovering the structure and key characteristics of data, often through the use of statistical graphics. These visual tools can reveal patterns and trends, and their effectiveness can be enhanced through interactivity. By enabling users to filter data, zoom, and toggle visual features, interactive plots can accelerate and enrich the EDA process. This study extends a previous graphical study by incorporating an interactive framework. Using a statistical lineup protocol with two target patterns (a linear trend and a clustering trend) participants interacted with plots by toggling various aesthetic features, including cluster coloring, ellipses …
Statistical Investigations Of Strategies In The Game Ecosystem, Dylan Li
Statistical Investigations Of Strategies In The Game Ecosystem, Dylan Li
Master's Theses
This work provides a probability-based analysis of strategies in the board game Ecosystem. Ecosystem is a turn-based multiplayer tiling game, where players take turns picking a wildlife card from a limited pool of cards then placing that card on their personal 4x5 grid. The objective of the game is to place the wildlife cards to maximize your score, as each card’s scoring condition depends on the presence or absence of certain cards surrounding it. The goal of this project is to determine optimal strategies for tiling your grid using techniques such as simulation to find optimal grid arrangements and clustering …
A System And Method For Measuring Spatially Varying Surface Appearances With A Study Of Feathers, Jessica Baron-Lis
A System And Method For Measuring Spatially Varying Surface Appearances With A Study Of Feathers, Jessica Baron-Lis
All Dissertations
Real-world materials, particularly biological structures such as feathers exhibit complex appearances that vary spatially across their surfaces. The field of computer graphics provides a means of understanding such surfaces through material modeling which uses both analytical models and data acquired from light-surface interactions. There are many efforts within the past decade in measuring materials for graphics, but common limitations in these works include not accounting for spatially varying properties and reliance on neural networks and synthetic datasets.
Feathers from modern birds present diverse appearances due to how light interacts with their unique hierarchical microstructures. Variations in those structures lead to …
Mortgage Default Classification Modeling For Variable Analysis, Brendan R. Goggins
Mortgage Default Classification Modeling For Variable Analysis, Brendan R. Goggins
Honors College Theses
The financial crisis of the early 2000’s is a prime example of the severe consequences that mortgage default and borrower insolvency can have on economies at large. Mortgage default specifically is a prime case with the popularization of mortgage backed securities and the commonality of this loan structure. Multiple hypotheses and models have been formed to understand the reasons, causes, and consequences of mortgage default. This paper uses both machine learning and statistical classification models to inform an understanding of the variables most significant and impactful to the default outcome of mortgages. Consideration is given to both loan-level microeconomic variables …
Analysis Of Sled Dog Biomechanics, Natalie Bender
Analysis Of Sled Dog Biomechanics, Natalie Bender
Williams Honors College, Honors Research Projects
This paper is an analysis of data collected by Dr Rachel Olson and her team. The data was collected from the same set of sled dogs before and after training for the Iditarod race. The goal of this paper is to draw conclusions on whether the gait of sled dogs’ change with fitness level. The data was cleaned in R to find the average peak for forelimb joint angles per run for each dog. The data was analyzed with 3 different ANOVAs – one including both the shoulder and carpus, one for just the shoulder, and one for just the …
Theoretical Foundations And Applied Performance Of Periodicity-Aware Imputation: Variable Bandpass Block Bootstrap Methods For Incomplete Time Series, Asmaa Ahmad
Electronic Theses & Dissertations (2024 - present)
Time series data are prevalent across a wide range of disciplines, including health surveillance, public policy, and environmental monitoring. In the presence of underlying cyclical patterns, the integrity of time series analysis depends critically on the ability to detect, model, and impute structured missing data without compromising the temporal structure. This dissertation introduces and validates a novel imputation framework that integrates the Variable Bandpass Periodic Block Bootstrap (VBPBB) into multiple imputation procedures, improving the accuracy, robustness, and interpretability of time series models under high rates of missingness and noise. The overarching goal of this dissertation was to develop and evaluate …
Striking A Balance: Market Shock & Responses In Automotive Components Manufacturing, Emma Lane Mcgahey
Striking A Balance: Market Shock & Responses In Automotive Components Manufacturing, Emma Lane Mcgahey
All Theses
This thesis examines the effects of extreme market shocks on supply chain dynamics within the automotive industry. Through an analysis of demand data from an automotive manufacturer to its component suppliers (January 2018 to May 2024), the study investigates the relationship between market shocks and supply chain responses, providing insights into how auto components inventory management handles downstream responses to market shocks. With supporting public data—from FRED, BLS, and the U.S. Census Bureau resources—we explore two primary relationships: the impact of market shocks on the Average Standard Deviation of Demand (SDO) and the effect of demand variability on expedited pricing …
Decoding Neural Networks: An Information-Theoretic Guide To Interpretability, Error Analysis And Efficiency, Mackenzie J. Meni
Decoding Neural Networks: An Information-Theoretic Guide To Interpretability, Error Analysis And Efficiency, Mackenzie J. Meni
Theses and Dissertations
This dissertation addresses critical challenges in neural network design by leveraging entropy-based techniques to improve model efficiency, interpretability, and bias reduction. Focusing on the unique demands of computer vision applications, particularly object detection and classification for real-time systems, this work introduces a series of innovative methods centered on information theory. At the core of these methods is the Probabilistic Explanations of Entropic Knowledge (PEEK) framework, a tool developed to analyze and visualize entropy distributions across feature maps. PEEK offers insights into information flow within neural networks, making it possible to pinpoint layers that contribute meaningfully to decision-making or identify those …
Evaluating Trauma-Informed Design In A Mental Health Setting: A Community-Based Research Case Study, Marie Spence
Evaluating Trauma-Informed Design In A Mental Health Setting: A Community-Based Research Case Study, Marie Spence
Electronic Theses and Dissertations
This case study utilized a community-based research framework to explore how the Trauma-Informed Design framework can be implemented in a mental health setting. This study focused on the site of Empower Therapy Practice, a private mental health practice in the Denver Metro Area, to engage clients and staff to participate in advisory boards and inform the interior design of a new office space. To explore the application of Trauma-Informed Design, participants engaged in a variety of research activities, including an evaluative questionnaire, Photovoice, and focus group. Advisory board members identified various aspects of Trauma-Informed Design which meaningfully translate to therapeutic …
The Naked Truth Of My Voice: Surveying The Soul Of An Aspiring Educator From Dusk To Dawn: An Arts-Based Auto-Criticism Inquiry, Siddharth Maan
The Naked Truth Of My Voice: Surveying The Soul Of An Aspiring Educator From Dusk To Dawn: An Arts-Based Auto-Criticism Inquiry, Siddharth Maan
Electronic Theses and Dissertations
This dissertation is based on auto-criticism, a new qualitative inquiry that combines educational criticism and arts-based research. It focuses on my own experiences as an aspiring educator who struggles with stuttering and public speaking anxiety. The study aims to describe, interpret, evaluate, and thematize my experiences of dealing with public speaking anxiety and stuttering before, during, and after classroom teaching. In addition, this dissertation highlights the potential contributions of auto-criticism as a methodology to qualitative research and higher education. I utilized journaling to document data. Photos and music were also used to enhance the understanding of my lived experiences and …
A Uniformly Most Powerful Test For The Mean Of A Beta Distribution, Richard Ntiamoah Kyei
A Uniformly Most Powerful Test For The Mean Of A Beta Distribution, Richard Ntiamoah Kyei
Electronic Theses and Dissertations
The beta distribution is used in numerous real-world applications, including areas such as manufacturing (quality control) and analyzing patient outcomes in health care. It also plays a key role in statistical theory, including multivariate analysis of variance (MANOVA) and Bayesian statistics. It is a flexible distribution that can account for many different characteristics of real data. To our surprise, there has been very little work or discussion on performing statistical hypothesis testing for the mean when it is reasonable to assume that the population is beta distributed. Many analysts conduct traditional analyses using a t-test or nonparametric approach, try transformations, …
Exploring Healthcare Chatbot Information Presentation: Applying Hierarchical Bayesian Regression And Inductive Thematic Analysis In A Mixed Methods Study, Samuel Nelson Koscelny
Exploring Healthcare Chatbot Information Presentation: Applying Hierarchical Bayesian Regression And Inductive Thematic Analysis In A Mixed Methods Study, Samuel Nelson Koscelny
All Theses
High blood pressure, also known as hypertension, significantly increases the risk of heart disease and stroke, which are leading causes of death in the United States. While contributing to over 691,000 deaths in 2021 alone in the United States (U.S.), it also imposes immense economic burden on the healthcare system, costing approximately $131 billion annually. One way to address this issue is for increased self-care behaviors and medication adherence, both of which require sufficient health literacy. Despite the importance of health literacy, 90% of U.S. adults struggle with health-related subjects. Overcoming the issues associated with health literacy requires addressing the …
Emotionality Stigma Scale: Measurement Development, Reliability, And Validity., Hayley D. Seely
Emotionality Stigma Scale: Measurement Development, Reliability, And Validity., Hayley D. Seely
Electronic Theses and Dissertations
Emotions are biological responses to stimuli that allow individuals to derive meaning, appraise experiences, and prepare to respond. However, individuals perceive emotions differently based on emotion socialization which not only dictates the way emotions are viewed and managed but also has been directly linked with mental health outcomes. Furthermore, research shows emotion socialization is informed by demographic variables such as gender such that the expectations of emotionality differ; where women are taught to express emotions, men are taught to conceal. Given the societal rules regarding emotionality, it is possible that emotionality stigma – the stigma around the experience and expression …
Comparing The Preparation Of Youth Services Librarians To Their On-The-Ground Experiences: A Grounded Theory Study Incorporating Criticism And Connoisseurship, Anne Holland
Electronic Theses and Dissertations
The purpose of this study was to better understand the on-the-ground preparation of youth services librarians, in contrast to their professional training in Master’s of Library Science (MLIS) programs. Classic Grounded Theory was the predominant methodology for this qualitative study, and elements of Criticism and Connoisseurship were also utilized. Document review, interviews, and journaling activities with ten participants were the primary methods of data collection. Key findings from this dissertation include a grounded theory explaining the current state of preparation for youth services librarianship, and multiple avenues for further study.
Extending The Utility Of Ant Colony Optimization Through The Incorporation Of An Intraclass Correlation Coefficient To Assess For Rater Consistency, Mark Leveling
Electronic Theses and Dissertations
Ant Colony Optimization (ACO) is a flexible algorithm designed to solve complex combinatorial problems. While the method was derived from the behavior of ants by researchers in the field of computer science, its application to solving complex combinatorial problems is widespread in a growing number of fields in behavioral science, including psychometrics. Over the last two decades, psychometricians have adapted ACO to measurement model specification problems with the intention of generating measurement models that express measurement model fit and reliability within the standards of what is considered acceptable. Additionally, psychometricians have used ACO to generate shortened versions of existing measures …
Recursive Marix Game Analysis: Optimal, Simplified, And Human Strategies In Brave Rats, William A. Medwid
Recursive Marix Game Analysis: Optimal, Simplified, And Human Strategies In Brave Rats, William A. Medwid
Master's Theses
Brave Rats is a short game with simple rules, yet establishing a comprehensive strategy is very challenging without extensive computation. After explaining the rules, this paper begins by calculating the optimal strategy by recursively solving each turn’s Minimax strategy. It then provides summary statistics about the complex, branching Minimax solution. Next, we examine six other strategy models and evaluate their performance against each other. These models’ flaws highlight the key elements that contribute to the effectiveness of the Minimax strategy and offer insight into simpler strategies that human players could mimic. Finally, we analyze 123 games of human data collected …
Towards A New Role Of Mitochondrial Hydrogen Peroxide In Synaptic Function, Cliyahnelle Z. Alexander
Towards A New Role Of Mitochondrial Hydrogen Peroxide In Synaptic Function, Cliyahnelle Z. Alexander
Student Theses and Dissertations
Aerobic metabolism is known to generate damaging ROS, particularly hydrogen peroxide. Reactive oxygen species (ROS) are highly reactive molecules containing oxygen that have the potential to cause damage to cells and tissues in the body. ROS are highly reactive atoms or molecules that rapidly interact with other molecules within a cell. Intracellular accumulation can result in oxidative damage, dysfunction, and cell death. Due to the limitations of H2O2 (hydrogen peroxide) detectors, other impacts of ROS exposure may have been missed. HyPer7, a genetically encoded sensor, measures hydrogen peroxide emissions precisely and sensitively, even at sublethal levels, during …
The Quantitative Analysis And Visualization Of Nfl Passing Routes, Sandeep Chitturi
The Quantitative Analysis And Visualization Of Nfl Passing Routes, Sandeep Chitturi
Computer Science and Computer Engineering Undergraduate Honors Theses
The strategic planning of offensive passing plays in the NFL incorporates numerous variables, including defensive coverages, player positioning, historical data, etc. This project develops an application using an analytical framework and an interactive model to simulate and visualize an NFL offense's passing strategy under varying conditions. Using R-programming and data management, the model dynamically represents potential passing routes in response to different defensive schemes. The system architecture integrates data from historical NFL league years to generate quantified route scores through designed mathematical equations. This allows for the prediction of potential passing routes for offensive skill players in response to the …
Selected Topics On Sequential Designs For Decision Making, Caroline Kerfonta
Selected Topics On Sequential Designs For Decision Making, Caroline Kerfonta
All Dissertations
This dissertation is comprised of three parts. The first proposes a sequential approach to determine the experimental setting with the minimum variance (Kerfonta et al., 2024). Two acquisition functions are developed to assist developing the approach. Theoretical results along with a case study using data from crystallization experiments is conducted to show the ability of the proposed method to correctly select the experiment with the minimum variance. The second and third parts propose adaptations to the Bayesian optimization algorithm using transformed additive Gaussian processes (TAG) as the surrogate model. The goal of using the TAG framework is to decompose the …
Phenomenological Inquiry Into Middle School Teachers’ Perception Of Creativity, Katalin Grajzel
Phenomenological Inquiry Into Middle School Teachers’ Perception Of Creativity, Katalin Grajzel
Electronic Theses and Dissertations
Researchers do agree that creativity is an ability that can be developed and should be fostered (Guilford, 1958; Parnes, 1961). Teachers play an important role in creativity development and often serve as gatekeepers to identify gifted and talented students (Bianco et al., 2011; Novak & Jones, 2021; Schack & Starko, 1990). However, teachers’ judgment of their students’ creativity often only correlates weakly with the results of creativity measures (Kettler et al., 2018; Torrance, 1963). Therefore, in this study I explored teachers’ perception of creativity and creative students as well as factors that support or hinder creativity. The findings revealed that …