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Articles 3571 - 3600 of 12812
Full-Text Articles in Statistics and Probability
We’Re Here To Get You There: A Statistical Analysis Of Bridgewater State University’S Transit System, Abigail Adams
We’Re Here To Get You There: A Statistical Analysis Of Bridgewater State University’S Transit System, Abigail Adams
Honors Program Theses and Projects
Bridgewater State University first established its on-campus transportation service in January of 1984. While it began only running as an on-campus service for students throughout the day, the service grew to expand by offering an off-campus connection to the neighboring city of Brockton and absorbed the night service system from the campus safety team. As BSU Transit continues to grow, the organization is seeking ways to improve their overall service and better prepare their fleet and driver pool to accommodate this growth. The purpose of this research is to analyze trends among the data collected by BSU Transit and assist …
A Study On Differing Generational Values And Expectations In Corporate America, Abigail Grella
A Study On Differing Generational Values And Expectations In Corporate America, Abigail Grella
Honors Program Theses and Projects
This paper examines the most common factors that lead to voluntary employee turnover, and the implications employee turnover has on an organization. Additionally, this paper will consider the varying values and workplace expectations of different demographic groups such as Millennials, Generation X, Generation Y, and Baby Boomers and how such factors could influence voluntary turnover. A study is conducted from survey results gathered across a large span of generations that are currently employed. Using statistical analysis employing t-tests and a Mood’s Median test, the results show that different generations have differently weighing values for specific organizational offerings. The results show …
Guidelines For Regression Analysis In Sas And R: A Case Study, Sarah Milligan
Guidelines For Regression Analysis In Sas And R: A Case Study, Sarah Milligan
Honors Program Theses and Projects
When a player is a free agent, an individual who is able to sign to any team, one wonders what their best option is. Will signing with Team A or Team B provide them with the largest salary? What factors will affect their salary the most? Does last year’s statistics have a strong impact on next year’s salary? These questions can be answered by performing a regression analysis on previous years data. The primary focus of this project is to determine the most important variables related to an NBA salary. Likewise, the statistical programs SAS and R will be compared …
Differences In Effectiveness And Use Of Laparoscopic Surgery In Locally Advanced Colon Cancer Patients, M. Schootman, Matthew Mutch, T. Loux, Jan M. Eberth Ph.D., N. O. Davidson
Differences In Effectiveness And Use Of Laparoscopic Surgery In Locally Advanced Colon Cancer Patients, M. Schootman, Matthew Mutch, T. Loux, Jan M. Eberth Ph.D., N. O. Davidson
Faculty Publications
Patients with locally advanced colon cancer have worse outcomes. Guidelines of various organizations are conflicting about the use of laparoscopic colectomy (LC) in locally advanced colon cancer. We determined whether patient outcomes of LC and open colectomy (OC) for locally advanced (T4) colon cancer are comparable in all colon cancer patients, T4a versus T4b patients, obese versus non-obese patients, and tumors located in the ascending, descending, and transverse colon. We used data from the 2013–2015 American College of Surgeons’ National Surgical Quality Improvement Program. Patients were diagnosed with nonmetastatic pT4 colon cancer, with or without obstruction, and underwent LC (n …
Neural Oscillatory Activity Serving Sensorimotor Control Is Regulated By The Mitochondrial Redox Environment In Health And Disease, Rachel Spooner
Neural Oscillatory Activity Serving Sensorimotor Control Is Regulated By The Mitochondrial Redox Environment In Health And Disease, Rachel Spooner
Theses & Dissertations
Despite effective regimens of combination antiretroviral therapy, individuals with HIV are still at higher risk for developing forms of cognitive impairment, with one of the most common behavioral abnormalities to manifest being motor dysfunction. This is an important consideration, as deficits in motor control likely contribute to higher-order cognitive impairments, which together, lead to functional dependencies in the ever-growing aging population of HIV-infected adults. While the neuroanatomical bases of motor dysfunction have recently been illuminated in people living with HIV (PLWH), there remains an open question regarding the molecular processes supporting the circuit-level neuronal dynamics that potentially serve these behavioral …
Time Series Forecasting Of Covid-19 Deaths In Massachusetts, Andrew Disher
Time Series Forecasting Of Covid-19 Deaths In Massachusetts, Andrew Disher
Honors Program Theses and Projects
The aim of this study was to use data provided by the Department of Public Health in the state of Massachusetts on its online dashboard to produce a time series model to accurately forecast the number of new confirmed deaths that have resulted from the spread of CoViD-19. Multiple different time series models were created, which can be classified as either an Auto-Regressive Integrated Moving Average (ARIMA) model or a Regression Model with ARIMA Errors. Two ARIMA models were created to provide a baseline forecasting performance for comparison with the Regression Model with ARIMA Errors, which used the number of …
Markov Model Composition Of Balinese Reyong Norot Improvisations, Taylor Flanagan, Robert Rovetti
Markov Model Composition Of Balinese Reyong Norot Improvisations, Taylor Flanagan, Robert Rovetti
Honors Thesis
Markov models are mathematical structures that model the transition between possible states based on the probability of moving from one state to any other. Thus, given a distribution of starting points, the model produces a chain of states that are visited in sequence. Such models have been used extensively to generate music based on probabilities, as sequences of states can represent sequences of notes and rhythms. While music generation is a common application of Markov models, most existing work attempts to reconstruct the musical style of classical Western composers. In this thesis, we produce a series of Markov chains that …
Application Of Randomness In Finance, Jose Sanchez, Daanial Ahmad, Satyanand Singh
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.
Cardiovascular Complications Of Systemic Lupus Erythematosus: Impact Of Risk Factors And Therapeutic Efficacy--A Tertiary Centre Experience In An Appalachian State, Elise Danielle Mcveigh, Amna Batool, Arnold J. Stromberg, Ahmed K. Abdel-Latif, Nayef Mohammed Kazzaz
Cardiovascular Complications Of Systemic Lupus Erythematosus: Impact Of Risk Factors And Therapeutic Efficacy--A Tertiary Centre Experience In An Appalachian State, Elise Danielle Mcveigh, Amna Batool, Arnold J. Stromberg, Ahmed K. Abdel-Latif, Nayef Mohammed Kazzaz
Statistics Faculty Publications
OBJECTIVES: Cardiovascular complications became a notable cause of morbidity and mortality in patients with lupus as therapeutic advancements became more efficient at managing other complications. The Appalachian community in Kentucky has a higher prevalence of traditional cardiovascular risk factors, predisposing them to cardiovascular events. Namely, the mean body mass index of the members of the Kentucky Appalachian community was reported at 33 kg/m2 and 94.3% of male members of this community use tobacco. We sought to identify risk factors that predispose patients with lupus to cardiovascular morbidities and examine the effect of immunomodulatory drugs.
METHODS: We identified 20 UKHS …
Confidence Intervals Of Covid-19 Vaccine Efficacy Rates, Frank Wang
Confidence Intervals Of Covid-19 Vaccine Efficacy Rates, Frank Wang
Numeracy
This tutorial uses publicly available data from drug makers and the Food and Drug Administration to guide learners to estimate the confidence intervals of COVID-19 vaccine efficacy rates with a Bayesian framework. Under the classical approach, there is no probability associated with a parameter, and the meaning of confidence intervals can be misconstrued by inexperienced students. With Bayesian statistics, one can find the posterior probability distribution of an unknown parameter, and state the probability of vaccine efficacy rate, which makes the communication of uncertainty more flexible. We use a hypothetical example and a real baseball example to guide readers to …
Species In Vernal Pools: Anova, Lisa Manne
Species In Vernal Pools: Anova, Lisa Manne
Open Educational Resources
A one-way analysis of variance exercise using data on species diversities from vernal pools.Data are from vernal pools in Willowbrook Park (adjacent to College of Staten Island's campus) in spring.
The typical ANOVA gives a straightforward result (significant anova, easily-interpreted Tukey-Kramer analysis). This data set requires more nuanced interpretation, as the ANOVA is marginally significant, and Tukey-Kramer yields one significant pairwise comparison between groups. Relative lack of variation within groups explains this apparent enigma.
Improving Bayesian Graph Convolutional Networks Using Markov Chain Monte Carlo Graph Sampling, Aneesh Komanduri
Improving Bayesian Graph Convolutional Networks Using Markov Chain Monte Carlo Graph Sampling, Aneesh Komanduri
Computer Science and Computer Engineering Undergraduate Honors Theses
In the modern age of social media and networks, graph representations of real-world phenomena have become incredibly crucial. Often, we are interested in understanding how entities in a graph are interconnected. Graph Neural Networks (GNNs) have proven to be a very useful tool in a variety of graph learning tasks including node classification, link prediction, and edge classification. However, in most of these tasks, the graph data we are working with may be noisy and may contain spurious edges. That is, there is a lot of uncertainty associated with the underlying graph structure. Recent approaches to modeling uncertainty have been …
Applying Emotional Analysis For Automated Content Moderation, John Shelnutt
Applying Emotional Analysis For Automated Content Moderation, John Shelnutt
Computer Science and Computer Engineering Undergraduate Honors Theses
The purpose of this project is to explore the effectiveness of emotional analysis as a means to automatically moderate content or flag content for manual moderation in order to reduce the workload of human moderators in moderating toxic content online. In this context, toxic content is defined as content that features excessive negativity, rudeness, or malice. This often features offensive language or slurs. The work involved in this project included creating a simple website that imitates a social media or forum with a feed of user submitted text posts, implementing an emotional analysis algorithm from a word emotions dataset, designing …
Retail Trading And Stock Volatility: The Case Of Robinhood, Cooper Jones
Retail Trading And Stock Volatility: The Case Of Robinhood, Cooper Jones
All Graduate Plan B and other Reports, Spring 1920 to Spring 2023
We examine the relation between Robinhood usership and stock market volatility. We show that daily fluctuations in Robinhood usership, which is used to proxy retail trading, significantly influence various measures of volatility. These results might suggest that Robinhood users contribute to noise trading as they are generally individuals trading on name recognition, media coverage, popularity, and familiarity of products, rather than on fundamental values. In our empirical approach, we find that the percentage increase in Robinhood usership Granger causes increases in daily stock volatility.
Randomised Trials At The Level Of The Individual, Jay J H. Park, Nathan Ford, Denis Xavier, Per Ashorn, Rebecca F. Grais, Zulfiqar Ahmed Bhutta, Herman Goossens, Kristian Thorlund, Maria Eugenia Socias, Edward J. Mills
Randomised Trials At The Level Of The Individual, Jay J H. Park, Nathan Ford, Denis Xavier, Per Ashorn, Rebecca F. Grais, Zulfiqar Ahmed Bhutta, Herman Goossens, Kristian Thorlund, Maria Eugenia Socias, Edward J. Mills
Centre of Excellence in Women and Child Health
In global health research, short-term, small-scale clinical trials with fixed, two-arm trial designs that generally do not allow for major changes throughout the trial are the most common study design. Building on the introductory paper of this Series, this paper discusses data-driven approaches to clinical trial research across several adaptive trial designs, as well as the master protocol framework that can help to harmonise clinical trial research efforts in global health research. We provide a general framework for more efficient trial research, and we discuss the importance of considering different study designs in the planning stage with statistical simulations. We …
Improving Access And Health Outcomes Through Carepartners And Medaccess Programs, Elora Way, Becky Wurwarg
Improving Access And Health Outcomes Through Carepartners And Medaccess Programs, Elora Way, Becky Wurwarg
Publications
Access to Care, a division of MaineHealth, works to ensure that Maine residents have access to comprehensive and affordable healthcare that improves community wellbeing. In 2020, as part of its ongoing commitment to evaluating the effectiveness of its programs, Access to Care partnered with the University of Southern Maine’s Data Innovation Project to conduct a multi-year retrospective evaluation of its two longest-running initiatives, CarePartners and MedAccess. Established in 2001, CarePartners coordinates donated healthcare services for low-income, uninsured residents across six Maine counties by connecting participants with case managers, primary care providers, and pharmacy benefits. Between 2016 and 2019, 4,426 individuals …
Applications Of Evidence Theory To High-Consequence Systems Safety, Christina Marie Deffenbaugh
Applications Of Evidence Theory To High-Consequence Systems Safety, Christina Marie Deffenbaugh
Mathematics & Statistics ETDs
Issues linked to abnormal environments (like high-consequence systems safety, e.g., nuclear weapon components, bridges, apartment buildings, etc.) may have insufficient information to use either classical statistical methods or Bayesian approaches for calculating associated probabilistic risks, so there is often a requirement for another method that can deal with a low-information situation to obtain a risk assessment. Belief/plausibility measures of uncertainty from A. P. Dempster and G. Shafer’s Evidence Theory is one such method. This thesis has two goals. First, a brief discussion on belief/plausibility measures as an application of Evidence Theory will familiarize the audience with its history and how …
Cointegration And Statistical Arbitrage Of Precious Metals, Judge Van Horn
Cointegration And Statistical Arbitrage Of Precious Metals, Judge Van Horn
Finance Undergraduate Honors Theses
When talking about financial instruments correlation is often thrown around as a measure of the relation between two securities. An often more useful or tradeable measure is cointegration. Cointegration is the measure of two securities tendency to revert to an average price over time. In other words, cointegration ignores directionality and only cares about the distance between two securities. For a mean reversion strategy such as statistical arbitrage cointegration proves to be a far more reliable statistical measure of mean reversion, and while it is more reliable than correlation it still has its own problems. One thing to consider is …
The Hybridizing Ions Treatment (Hit) Method Development And Computational Study On Sars-Cov-2 E Protein., Shengjie Sun
The Hybridizing Ions Treatment (Hit) Method Development And Computational Study On Sars-Cov-2 E Protein., Shengjie Sun
Open Access Theses & Dissertations
Fast and accurate calculations of the electrostatic features for highly charged biomolecules such as DNA, RNA, highly charged proteins, are crucial but challenging tasks. Traditional implicit solvent methods calculate the electrostatic features fast, but they are not able to balance the high net charges in the biomolecules effectively. Explicit solvent methods add unbalanced ions to neutralize the highly charged biomolecules in molecular dynamic simulations, which require more expensive computing resources. Here we developed a novel method, the Hybridizing Ions Treatment (HIT) method, which hybridizes the implicit solvent method with the explicit method to realistically calculate the electrostatic potential for highly …
Robust Variable Selection In Multiple Linear Regression Via Penalized Least Trimmed Squares., Reagan Kesseku
Robust Variable Selection In Multiple Linear Regression Via Penalized Least Trimmed Squares., Reagan Kesseku
Open Access Theses & Dissertations
Variable selection has been studied using different approaches. Its growing importance lies in numerous applications to high-dimensional data from experiments and natural phenomena. Often, models are to be constructed from such data based on significant variables for estimation or prediction purposes. This demands not just any variable selectionmethod, but one that is robust, computationally efficient and with other desirable statistical properties. Besides the high-dimensionality of such data, the presence of outliers is common due to heterogeneous sources. Though outliers often contain useful information, they can unduly influence non-robust estimators to produce misleading results. This is the case for ordinary least …
A Data Adaptive Model For Retail Sales Of Electricity, Johanna Marcelia
A Data Adaptive Model For Retail Sales Of Electricity, Johanna Marcelia
Boise State University Theses and Dissertations
When fitting a model to a data set, the goal is to create a model that captures the trends present in the data. However, data often contains regions where the underlying model changes or exhibits shifts in certain parameters due to economic events. These locations in the data are known as changepoints, and ignoring them can result in high error and incorrect forecasts. By developing a specific cost function and optimizing using the genetic algorithm, we are able to locate and account for the changepoints in a given data set. We specifically apply this process to the retail sales of …
Joint Spacing In The Caples Lake Granodiorite Of The Sierra Nevada Batholith In Eldorado National Forest, California: A Comparative Analysis Of Joint Sets And Data Resolution, Jimmy Wood
Theses/Capstones/Creative Projects
Joints are the most common deformation structure in the Earth’s upper crust and exert a significant influence on structural stability, landscape morphology, and fluid flow . Therefore, a greater understanding of fracture parameters (e.g., length, aperture, etc.) allows us to more accurately predict their presence, persistence, and prevalence, in the subsurface . We study the fracture spacing of two sub-orthogonal joint sets—66 NE-246 SW and 330 NW-150 SE—in the Caples Lake granodiorite of the Sierra Nevada Batholith, California. Specifically, we investigate 1) their spacing distributions with a keen interest in power-law (fractal) spacing, 2) distribution comparisons between master and cross …
Biases And Blind-Spots In Genome-Wide Crispr-Cas9 Knockout Screens, Merve Dede
Biases And Blind-Spots In Genome-Wide Crispr-Cas9 Knockout Screens, Merve Dede
Dissertations and Theses (Open Access)
Adaptation of the bacterial CRISPR-Cas9 system to mammalian cells revolutionized the field of functional genomics, enabling genome-scale genetic perturbations to study essential genes, whose loss of function results in a severe fitness defect. There are two types of essential genes in a cell. Core essential genes are absolutely required for growth and proliferation in every cell type. On the other hand, context-dependent essential genes become essential in an environmental or genetic context. The concept of context-dependent gene essentiality is particularly important in cancer, since killing cancer cells selectively without harming surrounding healthy tissue remains a major challenge. The toxicity of …
Estimating Cumulative Incidence Rate On Interval Censored Data In An Illness-Death Model., Chen Qian
Estimating Cumulative Incidence Rate On Interval Censored Data In An Illness-Death Model., Chen Qian
Electronic Theses and Dissertations
Phase IV clinical trials are designed to monitor long-term side effects caused overtime by the medical treatment. For instance, in advanced primary cancer treatment, childhood cancer survivors are often at risk of developing undesired events, such as cardiotoxicity, during their adulthood. Such problems could be due to their cancer or the treatment they received for their cancer such as radiation or intensive chemotherapy. Cardiotoxicity can be diagnosed with electrophysiology with measurements of fraction shortening, afterload, etc. Often the primary focus of a study could be on estimating the cumulative incidence of a particular outcome of interest such as cardiotoxicity. However, …
Observational Studies In Group Testing And Potential Applications., Alexander Christopher Noll
Observational Studies In Group Testing And Potential Applications., Alexander Christopher Noll
Electronic Theses and Dissertations
The use of group testing to identify individuals with targeted outcomes in a population can greatly improve the efficiency, speed, and cost effectiveness of testing a population for an outcome, or at least for identifying the prevalence of an outcome in a population. The implementation of causal inference techniques can provide the basis for an observational study that would allow an investigator to gather estimates for treatment effectiveness if group testing was conducted on the population in a certain way. This thesis examines a simulation of the above outlined principles in order to demonstrate a potential application for determining treatment …
High-Dimensional Random Forests, Roland Fiagbe
High-Dimensional Random Forests, Roland Fiagbe
Open Access Theses & Dissertations
The significant advances in technology have enabled easy collection and management of high-dimensional data in many fields, however, the process of modeling these data imposes a huge problem in the field of data science. Dealing with high-dimensional data is one of the significant challenges that degenerate the performance and precision of most classification and regression algorithms, e.g., random forests. Random Forest (RF) is among the few methods that can be extended to model high-dimensional data; nevertheless, its performance and precision, like others, are highly affected by high dimensions, especially when the dataset contains a huge number of noise or noninformative …
Gene Selection And Classification In High-Throughput Biological Data With Integrated Machine Learning Algorithms And Bioinformatics Approaches, Abhijeet R Patil
Gene Selection And Classification In High-Throughput Biological Data With Integrated Machine Learning Algorithms And Bioinformatics Approaches, Abhijeet R Patil
Open Access Theses & Dissertations
With the rise of high throughput technologies in biomedical research, large volumes of expression profiling, methylation profiling, and RNA-sequencing data are being generated. These high-dimensional data have large number of features with small number of samples, a characteristic called the "curse of dimensionality." The selection of optimal features, which largely affects the performance of classification algorithms in machine learning models, has led to challenging problems in bioinformatics analyses of such high-dimensional datasets. In this work, I focus on the design of two-stage frameworks of feature selection and classification and their applications in multiple sets of colorectal cancer data. The first …
Making Valid Inferences With Decision Tree, George Ekow Quaye
Making Valid Inferences With Decision Tree, George Ekow Quaye
Open Access Theses & Dissertations
HypoThesis testing and Confidence Interval (CI) estimates are key statistics in predicting future values in data analysis. Most often, CI estimates are directly obtained from the summary statistics of a particular statistical methodology output. However, when it comes to the summary of decision tree outputs, these CI estimates are not directly obtained. So a na\"{i}ve way of making node-level inference is to construct a $(1-\alpha) \times 100\%$ confidence interval for a node mean $\bar{y}_t$ using the relation: $\bar{y}_t \, \pm \, z_{1-\alpha/2} \, \frac{s_t}{\sqrt{n_t}}$, where $\bar{y}_t$ is the node mean and $s_t$ is the standard deviation estimates from the decision …
Refined Moderation Analysis With Binary Outcomes, Eric Anto
Refined Moderation Analysis With Binary Outcomes, Eric Anto
Open Access Theses & Dissertations
With the growing interest in personalized or precision medicine, it is indispensable thatmoderation analysis which is primarily related to the study of differential treatment effects among patients with different characteristics, also serves as the bedrock for precision medicine is taken more seriously. Concerning moderation analysis with binary outcomes, we start with an interesting observation, which shows that heterogeneous treatment effects could be equivalently estimated via a role exchange between the outcome and the treatment variable. The result holds for both experimental data and observational data, yet with an important difference in interpretation. Two estimators of moderating effects corresponding to two …
The Effects Of The Nba Covid Bubble On The Nba Playoffs: A Case Study For Home-Court Advantage, Michael Price
The Effects Of The Nba Covid Bubble On The Nba Playoffs: A Case Study For Home-Court Advantage, Michael Price
Honors Scholar Theses
The 2020 NBA playoffs were played inside of a bubble in Disney World because of the COVID-19 pandemic. This meant that there were no fans in attendance, games played on neutral courts and no traveling for teams, which in theory removes home-court advantage from the games. This setting has attracted much discussion as analysts and fans debated the possible effects it may have on the outcome of games. Home-court advantage has historically played an influential role in NBA playoff series outcomes. The 2020 playoff provided a unique opportunity to study the effects of the bubble and home-court advantage by comparing …