Statistics and Probability Commons^™

Using Natural Language Processing To Quantify The Efficacy Of Language Simplification As A Communication Strategy, Brian Nalley

All Graduate Theses and Dissertations

People with communication disorders often experience difficulties being understood by unfamiliar listeners or in noisy environments. A common strategy for effectively communicating in these scenarios is to use simpler and more predictable language. Despite the prevalence of this strategy, there has been little to no research to date focused on the effectiveness of language simplification as a communication strategy. This study seeks to begin filling that gap by using natural language processing to determine whether speakers with early-stage Parkinson’s disease and age-matched neurotypical speakers are able to successfully simplify their language while still maintaining the original message.

Simplification was measured …

Stressor: An R Package For Benchmarking Machine Learning Models, Samuel A. Haycock

All Graduate Theses and Dissertations

Many discipline specific researchers need a way to quickly compare the accuracy of their predictive models to other alternatives. However, many of these researchers are not experienced with multiple programming languages. Python has recently been the leader in machine learning functionality, which includes the PyCaret library that allows users to develop high-performing machine learning models with only a few lines of code. The goal of the stressor package is to help users of the R programming language access the advantages of PyCaret without having to learn Python. This allows the user to leverage R’s powerful data analysis workflows, while simultaneously …

Statistical Graph Quality Analysis Of Utah State University Master Of Science Thesis Reports, Ragan Astle

All Graduate Theses and Dissertations

Graphical software packages have become increasingly popular in our modern world, but there are concerns within the statistical visualization field about the default settings provided by these packages, which can make it challenging to create good quality graphs that align with standard graph principles. In this thesis, we investigate whether the quality of graphs from Utah State University (USU) Plan A Master of Science (MS) thesis reports from the years 1930 to 2019 was affected by the rise of graphical software packages. We collected all data stored on the USU Digital Commons website since November 2021 to determine the specific …

A Multivariate Investigation Of The Motivational, Academic, And Well-Being Characteristics Of First-Generation And Continuing-Generation College Students, Christopher L. Thomas, Staci Zolkoski

Journal of Research Initiatives

Prior research has noted differences in motivational, academic, and well-being factors between first-generation and continuing-education students. However, past investigations have primarily overlooked the interactive influence of protective and risk factors when comparing the characteristics of first-generation and continuing-education students. Thus, the current study adopted a multivariate approach to gain a more nuanced understanding of the influence of generational status on students' self-regulated learning capabilities, academic anxiety, sense of belonging, academic barriers, mental health concerns, and satisfaction with life. University students (N = 432, 67.46% Caucasian, 87.55% female, _Age = 28.10 ± 9.46) completed the Cognitive Test Anxiety Scale-2^{nd …}

On Image Response Regression With High-Dimensional Data, Noah Fuerth

Major Papers

A recent issue in statistical analysis is modelling data when the effect variable

changes at different locations. This can be difficult to accomplish when the dimensions

of the covariates are very high, and when the domain of the varying coefficient

functions of predictors are not necessarily regular. This research paper will investigate

a method to overcome these challenges by approximating the varying coefficient

functions using bivariate splines. We do this by splitting the domain of the varying

coefficient functions into a number of triangles, and build the bivariate spline functions

based on this triangulation. This major paper will outline detailed …

On Maximum Likelihood Estimators For A Jump-Type Affine Diffusion Two-Factor Model, Jiaming Yin Mr.

Major Papers

We consider a jump-type two-factor affine diffusion model driven by a subordinator in the context of continuous time observations. We study the asymptotic properties of the maximum likelihood estimator (MLE) for the drift parameters. In particular, we prove the strong consistency and the asymptotic normality of MLE in the subcritical case. We also present some numerical illustrations to confirm the theoretical results. The main difficulty of this major paper consists in proving the ergodicity of the model in the subcritical case and deriving the limiting behavior of the process.

A Characterization Of Complex-Valued Random Variables With Rotationally-Invariant Moments, Michael L. Maiello

Rose-Hulman Undergraduate Mathematics Journal

A complex-valued random variable Z is rotationally invariant if the moments of Z are the same as the moments of W=e^{i*theta}Z. In the first part of the article, we characterize such random variables, in terms of "vanishing unbalanced moments," moment and cumulant generating functions, and polar decomposition. In the second part, we consider random variables whose moments are not necessarily finite, but which have a density. In this setting, we prove two characterizations that are equivalent to rotational invariance, one involving polar decomposition, and the other involving entropy. If a random variable has both a density and moments which determine …

Creating Regression Model For Non-Markov Transition Probability Using Pseudo-Observations, Michael Gray

Dissertations and Theses

A multi-state model is a graphical tool widely used to illustrate a transitional relationship between states in many applications. We will study the transition probabilities of an illness-death model, which is an example of a multi-state model. We will investigate transition probabilities using a counting process approach. Aalen-Johansen estimator is the gold-standard in estimating a transition probability. However, Aalen-Johansen estimator may be biased when the Markov assumption is violated. Therefore, Aalen-Johansen estimator is an unreliable estimator when the Markov assumption is violated. Several papers have published non-parametric estimators that accommodate for non-Markov models using a counting process approach.

Furthermore, there …

Identifying Advantages To Teaching Linear Regression In A Modeling And Simulation Introductory Statistics Curriculum, Kit Harris Clement

Dissertations and Theses

Statistical association is a key facet of statistical literacy: claims based on relationships between variables or ideas rooted in data are found everywhere in media and discourse. A key development in introductory statistics curricula is the use of simulation-based inference, which has shown positive outcomes for students, especially in regards to statistical literacy and conceptual understanding. In this dissertation project, I investigate students from the Change Agents for the Teaching and Learning of STatistics (CATALST) curriculum in activities I designed for learning statistical association and linear regression. First, I analyzed the informal line fitting strategies of CATALST students. Findings suggest …

Modeling And A Domain Decomposition Method With Finite Element Discretization For Coupled Dual-Porosity Flow And Navier–Stokes Flow, Jiangyong Hou, Dan Hu, Xuejian Li, Xiaoming He

Mathematics and Statistics Faculty Research & Creative Works

In This Paper, We First Propose and Analyze a Steady State Dual-Porosity-Navier–Stokes Model, Which Describes Both Dual-Porosity Flow and Free Flow (Governed by Navier–Stokes Equation) Coupled through Four Interface Conditions, Including the Beavers–Joseph Interface Condition. Then We Propose a Domain Decomposition Method for Efficiently Solving Such a Large Complex System. Robin Boundary Conditions Are Used to Decouple the Dual-Porosity Equations from the Navier–Stokes Equations in the Coupled System. based on the Two Decoupled Sub-Problems, a Parallel Robin-Robin Domain Decomposition Method is Constructed and Then Discretized by Finite Elements. We Analyze the Convergence of the Domain Decomposition Method with the Finite …

(R2051) Analysis Of Map/Ph1, Ph2/2 Queueing Model With Working Breakdown, Repairs, Optional Service, And Balking, G. Ayyappan, G. Archana

Applications and Applied Mathematics: An International Journal (AAM)

In this paper, a classical queueing system with two types of heterogeneous servers has been considered. The Markovian Arrival Process (MAP) is used for the customer arrival, while phase type distribution (PH) is applicable for the offering of service to customers as well as the repair time of servers. Optional service are provided by the servers to the unsatisfied customers. The server-2 may get breakdown during the busy period of any type of service. Though the server- 2 got breakdown, server-2 has a capacity to provide the service at a slower rate to the current customer who is receiving service …

(R2053) Analysis Of Map/Ph/1 Queueing Model Subject To Two-Stage Vacation Policy With Imperfect Service, Setup Time, Breakdown, Delay Time, Phase Type Repair And Reneging Customer, N. Arulmozhi

Applications and Applied Mathematics: An International Journal (AAM)

In this paper, we study a continuous-time single server queueing system with an infinite system of capacity, a two-stage vacation policy with imperfect service, setup, breakdown, delay time, phase-type of repair and customer reneging. The Markovian Arrival Process is used for the arrival of a customer and the phase-type distribution is used when offering service. This encompasses the policy of two vacations: a single working vacation and multiple vacations. Using the Matrix-Analytic Method to approach the system generates an invariant probability vector for this model. Henceforth, the busy period, waiting time distribution and cost analysis are the additional findings. The …

(R2025) Improving The Lda Linear Discriminant Analysis Method By Eliminating Redundant Variables For The Diagnosis Of Covid-19 Patients, Kianoush Fathi Vajargah, Hamid Mottaghi Golshan, Fazel Badakhshan Farahabadi

Applications and Applied Mathematics: An International Journal (AAM)

Nowadays, with the increase in data production speed, the process of data analysis has faced many problems because this big data is often accompanied by plug-in data and redundant data. Therefore, the use of dimensional methods in the pre-data analysis stage is necessary. In data mining, dimensional reduction is one of the most important steps in data pre-processing. Principal component analysis (PCA) and linear discriminant analysis (LDA) are often used to reduce dimensions in data mining. The LDA method is a monitored and controlled method but the PCA is not controlled method. When the number of samples in classes is …

Population Modeling With Machine Learning Can Enhance Measures Of Mental Health - Open-Data Replication, Ty Easley, Ruiqi Chen, Kayla Hannon, Rosie Dutt, Janine Bijsterbosch

Statistical and Data Sciences: Faculty Publications

Efforts to predict trait phenotypes based on functional MRI data from large cohorts have been hampered by low prediction accuracy and/or small effect sizes. Although these findings are highly replicable, the small effect sizes are somewhat surprising given the presumed brain basis of phenotypic traits such as neuroticism and fluid intelligence. We aim to replicate previous work and additionally test multiple data manipulations that may improve prediction accuracy by addressing data pollution challenges. Specifically, we added additional fMRI features, averaged the target phenotype across multiple measurements to obtain more accurate estimates of the underlying trait, balanced the target phenotype's distribution …

Characterization Of Boreal-Arctic Vegetation Growth Phases And Active Soil Layer Dynamics In The High-Latitudes Of North America: A Study Combining Multi-Year In Situ And Satellite-Based Observations, Michael G. Brown

Dissertations, Theses, and Capstone Projects

This dissertation examined the seasonal freeze/thaw activity in boreal-Arctic soils and vegetation physiology in Alaska, USA and Alberta, Canada, using in situ environmental measurements and passive microwave satellite observations. The boreal-Arctic high-latitudes have been experiencing ecosystem changes more rapidly in comparison to the rest of Earth due to the presently warming climatic conditions having a magnified effect over Polar Regions. Currently, the boreal-Arctic is a carbon sink; however, recent studies indicate a shift over the next century to become a carbon source. High-latitude vegetation and cold soil dynamics are influenced by climatic shifts and are largely responsible for the regions …

Asymptotic Stability Of Solitary Waves For The 1d Nls With An Attractive Delta Potential, Satoshi Masaki, Jason Murphy, Jun Ichi Segata

Mathematics and Statistics Faculty Research & Creative Works

We Consider the One-Dimensional Nonlinear Schrödinger Equation with an Attractive Delta Potential and Mass-Supercritical Nonlinearity. This Equation Admits a One-Parameter Family of Solitary Wave Solutions in Both the Focusing and Defocusing Cases. We Establish Asymptotic Stability for All Solitary Waves Satisfying a Suitable Spectral Condition, Namely, that the Linearized Operator Around the Solitary Wave Has a Two-Dimensional Generalized Kernel and No Other Eigenvalues or Resonances. in Particular, We Extend Our Previous Result [35] Beyond the Regime of Small Solitary Waves and Extend the Results of [19, 29] from Orbital to Asymptotic Stability for a Suitable Family of Solitary Waves.

Statistical And Biological Analyses Of Acoustic Signals In Estrildid Finches, Moises Rivera

Dissertations, Theses, and Capstone Projects

Acoustic communication is a process that involves auditory perception and signal processing. Discrimination and recognition further require cognitive processes and supporting mechanisms in order to successfully identify and appropriately respond to signal senders. Although acoustic communication is common across birds, classical research has largely disregarded the perceptual abilities of perinatal altricial taxa. Chapter 1 reviews the literature of perinatal acoustic stimulation in birds, highlighting the disproportionate focus on precocial birds (e.g., chickens, ducks, quails). The long-held belief that altricial birds were incapable of acoustic perception in ovo was only recently overturned, as researchers began to find behavioral and physiological evidence …

(R1975) Map/Ph(1), Ph(2)/2 Queue With Multiple Vacation, Optional Service, Consultations And Interruptions, G. Ayyappan, S. Sankeetha

Applications and Applied Mathematics: An International Journal (AAM)

Two types of services are explored in this paper: regular server and main server, both of which provide both regular and optional services. Customers arrive using the Markovian Arrival Process (MAP), and service time is allocated based on phase type. The regular server uses the main server as a resource. Customers’ service at the primary server is disrupted as a result. When the queue size is empty, the main server can take several vacations. This system has been represented as a QBD Process that investigates steady state with the use of matrix analytic techniques, employing finite-dimensional block matrices. Our model’s …

Data-Optimized Spatial Field Predictions For Robotic Adaptive Sampling: A Gaussian Process Approach, Zachary Nathan

Computer Science Senior Theses

We introduce a framework that combines Gaussian Process models, robotic sensor measurements, and sampling data to predict spatial fields. In this context, a spatial field refers to the distribution of a variable throughout a specific area, such as temperature or pH variations over the surface of a lake. Whereas existing methods tend to analyze only the particular field(s) of interest, our approach optimizes predictions through the effective use of all available data. We validated our framework on several datasets, showing that errors can decline by up to two-thirds through the inclusion of additional colocated measurements. In support of adaptive sampling, …

Statistical Methods To Generate Artificial Slot Floor Data For The Advancement Of Casino Related Research, Courtney Bonner, Anastasia (Stasi) D. Baran, Jason D. Fiege, Saman Muthukumarana

International Conference on Gambling & Risk Taking

Abstract:

A common difficulty when researching gambling topics is the availability of high-quality data sets for development and testing. Due to the high level of secrecy within the gambling industry, if data is obtained for research purposes it is often prohibitively obfuscated, incomplete, or aggregated. Although these data have allowed for advancement in academic work, it leaves both the researchers and readers left wondering about what would be possible if more detailed data sets were available. To mitigate the paucity of data available to researchers, we present a Markov chain-based statistical process for producing artificial event data for a simulated …