Statistics and Probability Commons^™

[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: …

Geographic Patterns Of Educational Achievement: A Methodological Case Study Of Regression Modeling Approaches, Leokadia Lipien

USF Tampa Graduate Theses and Dissertations

This methodological case study introduces a novel approach to investigate the impact of student, teacher, and geographic factors on the academic achievement of virtual school students in Florida. Traditional linear regression models, and even multilevel models, often overlook spatial dependencies, which can lead to biased estimates and incomplete inferences. This research addresses this limitation by comparing a cross-classified multilevel model (CCMM) with a novel cross-classified spatial model (CCSM) that incorporates coefficients from geographically weighted regression (GWR). Utilizing secondary data from a statewide virtual school, including student demographics, teacher characteristics, and standardized test scores, along with U.S. Census Bureau data, the …

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.

The Gender Pay Gap: An Occupational Analysis (2012-2023), Curtis Long

Harriet L Wilkes Honors College Theses 2020 - Present

This thesis examines the gender wage gap across thirty major U.S. occupations from 2014 to 2023 using data from the Current Population Survey (CPS), more specifically, the U.S. Bureau of Labor Statistics (BLS). The analysis measures the difference in median weekly earnings between women and men in each occupation and applies two statistical tests: a yearly z-test to evaluate whether the average wage gap is significant, and a ten-year t-test to identify persistent occupational gaps. Results show significant wage differences in every year, with the largest disparities in finance, management, and law, and smaller gaps in education and healthcare. Consistent …

(Si15-140) Designing Bayesian Double Sampling Plans Based On Zero Inflated Poisson Distribution, Priyadharshini R., Shalini K., Hemalatha R., Sangeetha S.

Applications and Applied Mathematics: An International Journal (AAM)

The implementation of attribute-based sampling inspection serves as a quality control technique used across numerous industries to evaluate items or workflow processes. When the data exhibits a substantial number of zero counts, the zero-inflated Poisson (ZIP) distribution serves as an effective model for accommodating this zero-inflation. Double sampling plan (DSP) is a quality check method where the decision to approve or decline a batch comes after examining two samples, providing more conclusive information compared to a single sample plan (SSP). In practice, effective decision-making regarding submitted lots considers both within-lot and between-lot variations, which can be addressed through the use …

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 …