Statistics and Probability Commons^™

Machine Learning Applications: Cell Tracking And Nonparametric Estimation Of Non-Smooth Divergences, Mina Mahbub Hossain

All Graduate Theses and Dissertations, Fall 2023 to Present

This thesis brings together two important research directions: how to compare different sets of data more accurately, and how to better understand how brain cancer cells move and change shape.

In the first part, we look at a problem in statistics: measuring how different two data sources are from each other. Traditional methods often make strong assumptions, which may not always hold in real situations. Our approach avoids those assumptions by using an ensemble method, a way of combining many weak estimators into one stronger result. This makes the method more flexible and reliable, especially when dealing with complex or …

Is Complexity Virtuous?, Ryan Elmore, Jack Strauss

Business Information and Analytics: Faculty Scholarship

(Kelly et al., 2024) show that increasing complexity in linear models, with potentially thousands of predictors, is "virtuous". Their work contradicts the dogma of model selection, including the Principles of Parsimony and Occam's Razor. They find that when the number of predictors far exceeds the number of observations, the bias-variance trade-off breaks down, the variance declines, and the Sharpe ratio increases. In the context of ridge regression, we find that very high complexity coupled with large penalty terms (excessive shrinkage) generate forecasts that converge to a rolling window of past returns. For example, we show the past twelve-month moving average …

Improving Glycemic Control Among Indonesian Urban Adults: A Digital And Behavioral Extension Of The Information–Motivation–Behavioral Skills Model, Imelda Appulembang

Kesmas

Management of type 2 diabetes mellitus (T2DM) in Indonesia continues to face challenges due to behavioral, informational, and technological gaps among patients. This study analyzed the influence of self-regulatory competence and information, motivation, family support, and digital health literacy on glycemic control behavior. A cross-sectional survey was conducted from February to April 2025 among 587 adults aged >30 years with T2DM enrolled in the Chronic Disease Management Program at primary health care in six major cities: Jakarta, Surabaya, Yogyakarta, Medan, Makassar, and Banjarmasin. Data were collected through structured questionnaires and analyzed using partial least squares structural equation modeling. The findings …

Benchmarking Dna Foundation Models For Genomic And Genetic Tasks, Haonan Feng, Lang Wu, Bingxin Zhao, Chad Huff, Jianjun Zhang, Jia Wu, Lifeng Lin, Peng Wei, Chong Wu

School of Medicine Faculty Publications

The rapid evolution of DNA foundation models promises to revolutionize genomics, yet comprehensive evaluations are lacking. Here, we present a comprehensive, unbiased benchmark of five models (DNABERT-2, Nucleotide Transformer V2, HyenaDNA, Caduceus-Ph, and GROVER) across diverse genomic and genetic tasks including sequence classification, gene expression prediction, variant effect quantification, and topologically associating domain (TAD) region recognition, using zero-shot embeddings. Our analysis reveals that mean token embedding consistently and significantly improves sequence classification performance, outperforming other pooling strategies. Model performance varies among tasks and datasets; while general purpose DNA foundation models showed competitive performance in pathogenic variant identification, they were less …

Tannin Supplementation Alters Foraging Behavior And Spatial Distribution In Beef Cattle, Bashiri Iddy Muzzo, R. Douglas Ramsey, Kelvyn Bladen, Juan J. Villalba

Wildland Resources Student Research

Beef production on chemically uniform grass monocultures can limit nutrient synchrony and contribute to uneven pasture use. We evaluated whether supplementing tannins with bioactive plant secondary compounds improves foraging dynamics and landscape use by beef cattle grazing a meadow bromegrass monoculture in ways aligned with rangeland sustainability. Twenty-four Angus cow–calf pairs were allocated to six 3.6-ha paddocks (four pairs/paddock), randomly assigned to Control (Ctrl; n = 3) or Tannin treatment (TT; n = 3). Animals received 1 kg/cow/day of DDGs, with TT receiving an added 0.4% tannins (2:1 condensed:hydrolyzable). Grazing occurred during four 15-day periods (July– September) across two years. …

Field Validation Of Multiple Species Distribution Models Shows Variation In Performance For Predicting Aedes Albopictus Distributions At The Invasion Edge, Anna V. Shattuck, Brandon D. Hollingsworth Ph.D., Jared Skrotzki, Scott R. Campbell, Christopher L. Romano, Courtney C. Murdock

Faculty Publications

Background

Climate and land use changes have resulted in range expansion of many species. In this shifting disease landscape, it is important to leverage tools that can predict the distributions of invading vectors to target surveillance and control efforts and identify at-risk populations. Species distribution models (SDMs) are used to predict ranges of invasive species; however, invasive species often violate assumptions of equilibrium and niche conservatism. Moreover, these studies are rarely validated using independent data.

Methods 

We use long-term surveillance data for Aedes albopictus, a highly invasive mosquito capable of transmitting several arboviruses, at its range edge to evaluate a …

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 …

On Some Algebraic And Dynamical Aspects Of Families Of Polynomials, Prabhakar Ratipal Yadav

Doctoral Theses

This thesis investigates several arithmetic and algebraic properties of polynomials, with a particular emphasis on irreducibility, monogenity, and the behaviour of iterated polynomial sequences. We first study truncated binomial polynomials over the rationals and establish new affirmative results concerning their irreducibility. A substantial part of the work develops a detailed analysis of Newton polygons under polynomial composition. These structural insights yield broad applications, including criteria for stability and eventual stability of large families of polynomials, as well as precise information about the degrees and number of irreducible factors appearing in their iterates. These ideas further connect to questions about ramification …

The Odds Don’T Lie: Mathematical Reasoning And Societal Ignorance In Don’T Look Up, Nysa Vedwan, Shane Carey

LASER Journal

In Adam McKay’s 2021 satirical sci-fi movie Don’t Look Up, two astronomers discover a comet heading directly toward Earth. Despite overwhelming evidence and near-certainty of global extinction, their warnings are ignored and ridiculed. This paper discusses the mathematical and scientific foundations of the movie’s social and political reception, and specifically focuses on orbital prediction and probabilistic modeling as they relate to public understanding of risk. This paper shows how data is often undermined by political and social dynamics, by connecting the fictional events of the movie with real-world crises like the COVID-19 pandemic and the climate emergency. In Don’t Look …

Spatially Mapped Statewide Estimated Potential Evapotranspiration Using An Efficient Surface Interpolation Method: A Case Study Of South Carolina, Sudhanshu S. Panda, Devendra M. Amatya, Ka Kit Liu, Augustine Muwamba, Timothy J. Callahan

Journal of South Carolina Water Resources

Potential evapotranspiration (PET) exhibits substantial spatial and temporal variability across large landscapes, necessitating site-specific estimation for accurate environmental and water resource assessments. However, obtaining PET or ET data for specific locations across an entire state remains challenging due to the limited number of weather stations and associated environmental datasets. This study aimed to develop an automated geospatial modeling framework to map PET distribution across South Carolina, USA, using PET estimated by the temperature-based Hargreaves–Samani (H–S) method with daily weather data from 59 NOAA stations. Because the accuracy of spatial interpolation depends on both the target variable and the desired spatial …

Latent Classification Of Time-Dependent Transition Rates In Longitudinal Binary Outcome Data, Joonha Chang, Wenyaw Chan

School of Public Health Faculty Publications

Continuous-time Markov chain (CTMC) models and latent classification methods are commonly used to analyze longitudinal categorical outcomes in medical research. While CTMC models are popular for their simplicity and effectiveness, their assumption of constant transition rates presents limitations in capturing dynamic behaviors. To address this, non-homogeneous continuous-time Markov chains (NH-CTMCs) have been developed, incorporating time-varying transition rates to enhance model flexibility. In this study, we leverage closed-form transition probabilities for a fully ergodic two-state NH-CTMC model and propose a latent class clustering approach to identify heterogeneous transition rate patterns within the population. We emphasize the potential advantages of these models …

Explainable Post-Operative Patients Recovery Prediction Following Elective Brain Tumor Resection: A Precision Medicine Approach, Eleanor Belkin

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

[Kyda] Biologically Grounded Surrogate-Driven Parameter Inference For Sparsely Observed Dynamical Systems, Joshua C. Macdonald

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

[Project Insight] Spatio-Temporal Analysis Of Domestic Violence In Puerto Rico, Phyllis Muniu

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Mentoring First-Year Stem Students Through Collaborative Research In The Haynes Scholars Program, Alex Capaldi, Laura Tipton

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

[Lele] Incorporating Physiological Constraints In Estimates Of Post-Prandial Insulin Secretion Rate, Justin K. Garrish, Christine L. Chan, Douglas Nychka, Cecilia Diniz Behn

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Correlation With Car Density In Urban Environments And Its Influence On Chronic Obstructive Pulmonary Disease (Copd) Rates In The United States, Daniel Barreiro-Torres, Kedai Cheng

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Statistical Challenges And Simulation Results For Pilot Clinical Trials, Weiliang Cen

USF Tampa Graduate Theses and Dissertations

Background: The effect size estimated from a pilot trial is often an inaccurate reflection of the true effect size observed in a large trial, leading to either underestimation or overestimation. Published data suggest that effect sizes from large trials are typically smaller than those reported in their corresponding pilot trials. To address this discrepancy, conservative or discount adjustment methods are widely recommended to modify pilot trial effect sizes when calculating sample sizes, thereby maintaining adequate statistical power. This study aims to assess effect sizes from both pilot and large trials and to evaluate the performance of existing adjustment methods.

Methods: …

Circulating Levels Of Insulin-Like Growth Factor I (Igf-I) And Risk Ofmultiple Myeloma: An Observational And Mendelian Randomisation Study, Yolanda Benavente, Sara Hermosa, Nikos Papadimitriou, Alyssa I. Clay-Gilmour Ph.D., Elizabeth E. Brown, Jonathan N. Hofmann, Nathaniel Rothman, Qing Lan, Sonja I. Berndt, Demetrius Albanes, Mark Purdue, Mitchell J. Machiela, Stephen J. Chanock, Parveen Bhatti, Wendy Cozen, Aaron Norman, Susan L. Slager, James R. Cerhan, Vincent Rajkumar, Shaji J. Kumar, Et. Al.

Faculty Publications

Evidence for an association between insulin-like growth factors (IGF) and multiple myeloma (MM) is inconsistent. We examined total IGF-I concentrations and risk of MM by combining baseline serological data among UK Biobank participants (n = 444 187; 732 incident MM) with a two-sample Mendelian randomisation (MR) analysis using identified genetic variants associated with circulating total IGF-I and IGF-binding protein 3 (IGFBP-3) in the InterLymph consortium (2434 MM and their 2567 controls). Finally, additional lymphoid neoplasm (LN) subtypes were included for comparison with the main hypothesis. Circulating IGF-I level was positively associated with MM risk Hazard ratio-HR-per one standard deviation-SD-increase …

Network Construction Using Sparse Gaussian Graphical Model Based On Gwas Summary Statistics, Megh Subedi, Xuewei Cao, Byung-Jun Kim, Qiuying Sha

Michigan Tech Publications

In genome-wide association studies (GWAS), thousands of genetic variants are tested to identify their associations with a phenotype. GWAS have identified many strongly associated genetic variants with phenotypes and have greatly enhanced our understanding of the genetic architecture of complex phenotypes and diseases. Joint analysis of multiple phenotypes can increase the overall statistical power to detect genetic associations and allows for the identification of pleiotropic loci. A phenotype-phenotype network (PPN) represents phenotypes as nodes and the relationships between them as edges, which allows for the visualization of complex relationships between phenotypes, making it easier to identify clusters and helps us …

Perspectives On Firearm Storage Conversations: Summary Of Health Care Provider Interviews And Parent Focus Group, Rachel M. Gallo Mph

Publications

This report summarizes perspectives from Maine parents who own firearms and health care providers on safe firearm storage and related conversations in health care settings. Through interviews and a parent focus group, the project explored how firearms are stored, what influences storage decisions, and how families and providers feel about discussing firearm safety. Parents emphasized the importance of responsible ownership, education, and individualized storage solutions, while identifying cost as a key barrier to safer storage options. Many health care providers expressed interest in addressing firearm safety but cited limited time, lack of training, and concerns about patient trust as challenges. …

‘Earth System Engineers’ And The Cumulative Impact Of Organisms In Deep Time, S. A. F. Darroch, M. M. Casey, A. T. Cribb, A. E. Bates, M. E. Clapham, D. L. Contreras, M. Craffey, I. A. P. Duijnstee, W. Gearty, N. J. Gotelli, M. J. Hamilton, R. F. Hayes, P. M. Hull, D. E. Ibarra, V. A. Korasidis, J. Lee, C. V. Looy, T. R. Lyson, B. Muddiman, P. D. Roopnarine, A. B. Shupinski, F. A. Smith, A. L. Stigall, C. P. Tomé, K. A. Turk, A. Villaseñor, P. J. Wagner, Steve C. Wang

Mathematics & Statistics Faculty Works

Understanding the role of humans as ‘ecosystem engineers’ requires a deep-time perspective rooted in evolutionary history and the fossil record. However, no conceptual framework exists for studying the rise of ecosystem engineering in deep time, requiring us to consider effects that fall outside the scope of traditional definitions. Here, we present a new framework applicable to both modern and ancient engineering-type effects. We propose a new term – ‘Earth system engineering’ – to describe biological processes that alter the structure and function of planetary spheres, and which combines core tenets of ecosystem engineering, niche construction, and legacy effects. We illustrate …

How Fair Workweek Laws Affect Labor Markets: A New York City Case Study, Joseph Pickens, Aaron Sojourner

Employment Research Newsletter

No abstract provided.

Adverse Childhood Experiences, Positive Childhood Experiences, And Digital Media Use Among Children And Adolescents In The United States, Elizabeth L. Crouch, Emma Boswell, Monique J. Brown Ph.D., Kevin J. Bennett

Publications

No abstract provided.

How Fair Workweek Laws Affect Labor Markets: A New York City Case Study, Joseph Pickens, Aaron Sojourner

Upjohn Institute Policy and Research Briefs

No abstract provided.

Teaching Statistical Literacy Through An Excel Class Project, Patricia Berchiolli, Omar Babun Codorniu

Faculty and Staff Publications & Presentations

Lynn University’s core curriculum, The Dialogues, enables students to develop critical thinking, communication, and innovation skills. As part of this curriculum, Introductory Statistics introduces students to key statistical concepts while showing how they can be applied in real-world situations using Excel. The highlight of the course is the Statistics Excel Project, where students create their own dataset with a mix of quantitative and qualitative variables. To keep the focus on learning statistical techniques rather than data collection, students use Excel’s random number generator for quantitative data, which also avoids the need for IRB approval. From there, they calculate statistical measures, …

The Effect Of Renewable Energy Consumption, Economic Growth, And Energy Use On Co₂ Emissions In Indonesia: An Ardl Analysis, Raihan Ahmad Mustofa, Mariam Kamila, Rininta Nurrachmi, Syifa Shafnastiara

Jurnal Kebijakan Ekonomi

Abstract This study examines the dynamic relationship between renewable energy consumption, total energy use, economic growth, and CO₂ emissions in Indonesia over the period 1990–2021 using an ARDL approach. The results show a stable long-run relationship with quick adjustment after shocks. In the long run, energy consumption is associated with higher CO₂ emissions, reflecting the continued dominance of fossil fuels. Renewable energy helps reduce emissions in the short term, but its long-term impact remains statistically insignificant. GDP does not show a significant effect, suggesting that meaningful decarbonization will require a more intensive shift in the energy mix.

Keywords: ARDL, renewable …

A Review Of Research And Practices On Teaching Data Visualizations For Blind And Visually Impaired Students, Shiya Cao

Statistical and Data Sciences: Faculty Publications

Around 36 million people in the world are blind and an additional 217 million have moderate to severe vision impairment. In higher education, four percent of 54,204 undergraduates who participated in the 2022 American College Health Association survey reported to be blind or have low vision. Those students frequently do not have access to data visualizations we generally teach and use in postsecondary statistics and data science classes. The design of those visualizations is premised on implicit assumptions about the user’s visual ability. Making data visualizations accessible to blind and visually impaired (BVI) people would help improve equity in higher …

Engr 597: Special Projects In Engineering Science - Data Analytics, Ali Behnood Ph.D., P.E., M., Asce

GMAS Course Syllabi

No abstract provided.

Smarter Disease Detection From Electronic Health Record Data: An End-To-End Ai-Augmented Pipeline For Computable Phenotyping, Dylan Owens

Statistical Science Theses and Dissertations

Electronic Health Records (EHR) contain a wealth of structured and unstructured patient data that can be leveraged for computable phenotyping, the process of algorithmically identifying patient cohorts with specific diseases or conditions. Traditional rule-based phenotyping approaches, while interpretable, often struggle with scalability, portability across institutions, and effective use of unstructured clinical narratives. Recent advances in large language models (LLMs) present new opportunities for synthesizing complex free-text information into concise, clinically meaningful representations. However, integrating LLMs into phenotyping workflows requires careful design to maintain transparency, interpretability, and measurable uncertainty—features essential for clinical adoption and downstream applications such as decision support.

We …