Statistics and Probability Commons^™

Endoscopic Ultrasound Features Of Multiple Endocrine Neoplasia Type 1-Related Versus Sporadic Pancreatic Neuroendocrine Tumors: A Single-Center Retrospective Study, Gianluca Tamagno, Vanessa Scherer, Alberto Caimo, Simona Bergmann, Peter Kann

Articles

Pancreatic neuroendocrine tumors (pNETs) can occur in patients with a familial syndrome either as multiple endocrine neoplasia type 1 (MEN-1) or as sporadic tumors. Endoscopic ultrasound (EUS) has become one of the first-line investigations for pNET characterization. The ultrasonographic features of pNETs may differ depending on the familial versus sporadic pathogenesis of the tumor. Therefore, the EUS findings could help and direct the definition of a pNET with an impact on the most appropriate diagnostic and ther- apeutic patient management. Methods: In this single-center retrospective study, we reviewed the EUS features of 94 pNETs from 37 MEN-1 patients and 15 …

Identification And Estimation In Panel Models With Overspecified Number Of Groups, Ruiqi Liu

Graduate Dissertations and Theses

In this thesis, we provide a simple approach to identify and estimate group structure in panel models by adapting the M-estimationmethod. We consider both linear and nonlinear panel models where the regression coefficients are heterogeneous across groups but homogeneous within a group and the group membership is unknown to researchers. The main result of the thesis is that under certain assumptions, our approach is able to provide uniformly consistent group parameter estimator as long as the number of groups used in estimation is not smaller than the true number of groups. We also show that, with probability approaching one, our …

The Psychology Of Baseball: How The Mental Game Impacts The Physical Game, Kiera Dalmass

Honors Scholar Theses

The purpose of this study was to find whether or not sports psychology can be effective. Baseball was chosen as the sport for the study because baseball can be analyzed for nearly every single factor of the game, with the exception of the mental readiness or state of the player when he steps onto the field. It therefore provides the optimal atmosphere to provide clinical and statistical support to the field of sports psychology. Despite the various, numerous pieces of literature that praise and show support for sports psychology, there hasn’t been clinical research to support it. Additionally, multiple sports …

Cognitive Virtual Admissions Counselor, Kumar Raja Guvindan Raju, Cory Adams, Raghuram Srinivas

SMU Data Science Review

Abstract. In this paper, we present a cognitive virtual admissions counselor for the Master of Science in Data Science program at Southern Methodist University. The virtual admissions counselor is a system capable of providing potential students accurate information at the time that they want to know it. After the evaluation of multiple technologies, Amazon’s LEX was selected to serve as the core technology for the virtual counselor chatbot. Student surveys were leveraged to collect and generate training data to deploy the natural language capability. The cognitive virtual admissions counselor platform is currently capable of providing an end-to-end conversational dialog to …

Comparative Study: Reducing Cost To Manage Accessibility With Existing Data, Claire Chu, Bill Kerneckel, Eric C. Larson, Nathan Mowat, Christopher Woodard

SMU Data Science Review

“Project Sidewalk” is an existing research effort that focuses on mapping accessibility issues for handicapped persons to efficiently plan wheelchair and mobile scooter friendly routes around Washington D.C. As supporters of this project, we utilized the data “Project Sidewalk” collected and used it to confirm predictions about where problem sidewalks exist based on real estate and crime data. We present a study that identifies correlations found between accessibility data and crime and housing statistics in the Washington D.C. metropolitan area. We identify the key reasons for increased accessibility and the issues with the current infrastructure management system. After a thorough …

Using Random Forests To Describe Equity In Higher Education: A Critical Quantitative Analysis Of Utah’S Postsecondary Pipelines, Tyler Mcdaniel

Butler Journal of Undergraduate Research

The following work examines the Random Forest (RF) algorithm as a tool for predicting student outcomes and interrogating the equity of postsecondary education pipelines. The RF model, created using longitudinal data of 41,303 students from Utah's 2008 high school graduation cohort, is compared to logistic and linear models, which are commonly used to predict college access and success. Substantially, this work finds High School GPA to be the best predictor of postsecondary GPA, whereas commonly used ACT and AP test scores are not nearly as important. Each model identified several demographic disparities in higher education access, most significantly the effects …

Evaluating The Efficacy Of Conditional Analysis Of Variance Under Heterogeneity And Non-Normality, Yan Wang, Thanh Pham, Diep Nguyen, Eun Sook Kim, Yi-Hsin Chen, Jeffrey Kromrey, Zhiyao Yi, Yue Yin

Journal of Modern Applied Statistical Methods

A simulation study was conducted to examine the efficacy of conditional analysis of variance (ANOVA) methods where the initial homogeneity of variance screening leads to the choice between the ANOVA F test and robust ANOVA methods. Type I error control and statistical power were investigated under various conditions.

Developing Methods Of Processing And Analyzing Genetic Data To Examine Tiger Salamander Population Structure, Dennis Dongmin Kim

Undergraduate Research Symposium 2018

Professor Heather Waye and her colleagues conducted a pilot study in 2014 to measure genetic diversity and dispersal pattern in a population of tiger salamanders in west-central Minnesota. The ultimate goal of this research was to analyze the genetic differences between tiger salamander larvae captured in breeding ponds within Pepperton Waterfowl Production Area to understand the population structure and movement patterns. They expected that ponds closer to each other would have more similar genetic information, and that genetic differences between ponds would increase with geographic distance. However, the initial analysis using standard techniques failed to uncover useful patterns in the …

Visualizing Statistical Data On United States Agriculture, Xingyao Xiao

Undergraduate Research Symposium 2018

Food is essential to life. The United States Department of Agriculture (USDA) plays an indispensable role in ensuring people have access to healthy food. However, the data on the USDA website is not easy to access. Users must download many files to get data about animals, crops, the weather, and so on. To make the data more accessible to the general public, I built a web-based application to help make the data easy to access, explore, and compare. My application integrates multiple datasets from USDA website to provide graphic visualizations that enable users to get the exact, specific data intervals …

Elementary/Middle School Pre-Service Teachers’ Understanding Of Variability And The Use Of Dynamical Statistical Software, Yaomingxin Lu

Research and Creative Activities Poster Day

A primary purpose of the study was to examine the effects of using dynamical statistical software (DSS) on prospective teachers’ (PSTs) understanding of statistical concepts, especially variability. Data were collected from PSTs enrolled in a probability and statistics course designed for prospective K-8 teachers. After initial analysis of the data using coding and classification schemes, we found the need to develop a more targeted framework to analyze students’ different levels of understanding. The variability framework (Garfield & Ben-Zvi, 2005) and the Structure of Observed Learning Outcomes (SOLO) taxonomy were then used in combination to develop a revised framework in order …

Quality Of Life During Treatment With Chemohormonal Therapy: Analysis Of E3805 Chemohormonal Androgen Ablation Randomized Trial In Prostate Cancer, Alicia K. Morgans, Yu-Hui Chen, Christopher J. Sweeney, David F. Jarrard, Elizabeth R. Plimack, Benjamin A. Gartrell, Michael A. Carducci, Maha Hussain, Jorge A. Garcia, David Cella, Robert S. Dipaola, Linda J. Patrick-Miller

Internal Medicine Faculty Publications

Purpose

Chemohormonal therapy with docetaxel and androgen deprivation therapy (ADT+D) for metastatic hormone-sensitive prostate cancer improves overall survival as compared with androgen deprivation therapy (ADT) alone. We compared the quality of life (QOL) between patients with metastatic hormone-sensitive prostate cancer who were treated with ADT+D and those who were treated with ADT alone.

Methods

Men were randomly assigned to ADT+ D (six cycles) or to ADT alone. QOL was assessed by Functional Assessment of Cancer Therapy-Prostate (FACT-P), FACT-Taxane, Functional Assessment of Chronic Illness Therapy-Fatigue, and the Brief Pain Inventory at baseline and at 3, 6, 9, and 12 months. The …

Clustering Biological Data With Self-Adjusting High-Dimensional Sieve, Josselyn Gonzalez

Theses and Dissertations

Data classification as a preprocessing technique is a crucial step in the analysis and understanding of numerical data. Cluster analysis, in particular, provides insight into the inherent patterns found in data which makes the interpretation of any follow-up analyses more meaningful. A clustering algorithm groups together data points according to a predefined similarity criterion. This allows the data set to be broken up into segments which, in turn, gives way for a more targeted statistical analysis. Cluster analysis has applications in numerous fields of study and, as a result, countless algorithms have been developed. However, the quantity of options makes …

The Validity Of Online Patient Ratings Of Physicians, Jennifer L. Priestley, Yiyun Zhou, Robert Mcgrath

Faculty Articles

Background: Information from ratings sites are increasingly informing patient decisions related to health care and the selection of physicians.

Objective: The current study sought to determine the validity of online patient ratings of physicians through comparison with physician peer review.

Methods: We extracted 223,715 reviews of 41,104 physicians from 10 of the largest cities in the United States, including 1142 physicians listed as “America’s Top Doctors” through physician peer review. Differences in mean online patient ratings were tested for physicians who were listed and those who were not.

Results: Overall, no differences were found between the online patient ratings based …

Waste Management By Waste: Removal Of Acid Dyes From Wastewaters Of Textile Coloration Using Fish Scales, S M Fijul Kabir

LSU Master's Theses

Removal of hazardous acid dyes by economical process using low-cost bio-sorbents from wool industry wastewaters is of a pressing need, since it causes skin and respiratory diseases and disrupts other environmental components. Fish scales (FS), a by-product of fish industry, a type of solid waste, are usually discarded carelessly resulting in pungent odor and environmental burden. In this research, the FS of black drum (Pogonias cromis) were used for the removal of acid dyes (acid red 1 (AR1), acid blue 45 (AB45) and acid yellow 127 (AY126)) from wool industry wastewaters by absorption process with a view to …

A Comparison Of Unsupervised Methods For Dna Microarray Leukemia Data, Denise Harness

Appalachian Student Research Forum

Advancements in DNA microarray data sequencing have created the need for sophisticated machine learning algorithms and feature selection methods. Probabilistic graphical models, in particular, have been used to identify whether microarrays or genes cluster together in groups of individuals having a similar diagnosis. These clusters of genes are informative, but can be misleading when every gene is used in the calculation. First feature reduction techniques are explored, however the size and nature of the data prevents traditional techniques from working efficiently. Our method is to use the partial correlations between the features to create a precision matrix and predict which …

Under The Influence, Leonardo Cavicchio

Honors Projects in Mathematics

The purpose of this Honors Capstone entitled Under the Influence is to assess the validity of claims concerning the possible influence of roommates on one another, concerning alcohol on college campuses. This will be done by examining data collected in a prior study conducted over a two-year period. This analysis will focus on how alcohol consumption changes in correlation with the personality factors of roommates over an extended period of time. This secondary analysis of de-identified data will focus on primary and secondary subquestions. The primary question that will be addressed with the data set collected from the University of …

A Comparison Of Machine Learning Algorithms For Prediction Of Past Due Service In Commercial Credit, Liyuan Liu M.A, M.S., Jennifer Lewis Priestley Ph.D.

Published and Grey Literature from PhD Candidates

Credit risk modeling has carried a variety of research interest in previous literature, and recent studies have shown that machine learning methods achieved better performance than conventional statistical ones. This study applies decision tree which is a robust advanced credit risk model to predict the commercial non-financial past-due problem with better critical power and accuracy. In addition, we examine the performance with logistic regression analysis, decision trees, and neural networks. The experimenting results confirm that decision trees improve upon other methods. Also, we find some interesting factors that impact the commercials’ non-financial past-due payment.

The Influence Of A Proposed Margin Criterion On The Accuracy Of Parallel Analysis In Conditions Engendering Underextraction, Justin M. Jones

Masters Theses & Specialist Projects

One of the most important decisions to make when performing an exploratory factor or principal component analysis regards the number of factors to retain. Parallel analysis is considered to be the best course of action in these circumstances as it consistently outperforms other factor extraction methods (Zwick & Velicer, 1986). Even so, parallel analysis could benefit from further research and refinement to improve its accuracy. Characteristics such as factor loadings, correlations between factors, and number of variables per factor all have been shown to adversely impact the effectiveness of parallel analysis as a means of identifying the number of factors …

Score Test And Likelihood Ratio Test For Zero-Inflated Binomial Distribution And Geometric Distribution, Xiaogang Dai

Masters Theses & Specialist Projects

The main purpose of this thesis is to compare the performance of the score test and the likelihood ratio test by computing type I errors and type II errors when the tests are applied to the geometric distribution and inflated binomial distribution. We first derive test statistics of the score test and the likelihood ratio test for both distributions. We then use the software package R to perform a simulation to study the behavior of the two tests. We derive the R codes to calculate the two types of error for each distribution. We create lots of samples to approximate …

A Convolutional Neural Network Model For Species Classification Of Camera Trap Images, Annie Casey

Mathematics Undergraduate Theses

The overall purpose of this study was to automate the manual process of tagging species found in camera trap images using machine learning. The basic design of this study was to implement a Convolutional Neural Network model in Python using the Keras and Tensorflow modules that learn to recognize patterns in images in order to classify what species is in a given image and to label it accordingly. Results of the analysis highlight the importance of a large sample size, the degree of accuracy according to various arguments in the model, effectiveness of multiple layers that include Max Pooling, and …

Physical Activity Across The Lifespan And Liver Cancer Incidence In The Nih-Aarp Diet And Health Study Cohort., Hannah Arem, Erikka Loftfield, Pedro F Saint-Maurice, Neal D Freedman, Charles E Matthews

Epidemiology Faculty Publications

While liver cancer rates in the United States are increasing, 5-year survival is only 17.6%, underscoring the importance of prevention. Physical activity has been associated with lower risk of developing liver cancer, but most studies assess physical activity only at a single point in time, often in midlife. We utilized physical activity data from 296,661 men and women in the NIH-AARP Diet and Health Study cohort to test whether physical activity patterns over the life course could elucidate the importance of timing of physical activity on liver cancer risk. We used group modeling of longitudinal data to create physical activity …

Factors Affecting The Number And Type Of Student Research Products For Chemistry And Physics Students At Primarily Undergraduate Institutions: A Case Study., Birgit Mellis, Patricia Soto, Chrystal D. Bruce, Graciela Lacueva, Anne Wilson, Rasitha Jayasekare

2018 Faculty Bibliography

For undergraduate students, involvement in authentic research represents scholarship that is consistent with disciplinary quality standards and provides an integrative learning experience. In conjunction with performing research, the communication of the results via presentations or publications is a measure of the level of scientific engagement. The empirical study presented here uses generalized linear mixed models with hierarchical bootstrapping to examine the factors that impact the means of dissemination of undergraduate research results. Focusing on the research experiences in physics and chemistry of undergraduates at four Primarily Undergraduate Institutions (PUIs) from 2004–2013, statistical analysis indicates that the gender of the student …

Direct Error Driven Learning For Deep Neural Networks With Applications To Bigdata, R. Krishnan, Jagannathan Sarangapani, V. A. Samaranayake

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, generalization error for traditional learning regimes-based classification is demonstrated to increase in the presence of bigdata challenges such as noise and heterogeneity. To reduce this error while mitigating vanishing gradients, a deep neural network (NN)-based framework with a direct error-driven learning scheme is proposed. To reduce the impact of heterogeneity, an overall cost comprised of the learning error and approximate generalization error is defined where two NNs are utilized to estimate the costs respectively. To mitigate the issue of vanishing gradients, a direct error-driven learning regime is proposed where the error is directly utilized for learning. It …

Developing Statistical Methods For Data From Platforms Measuring Gene Expression, Gaoxiang Jia

Statistical Science Theses and Dissertations

This research contains two topics: (1) PBNPA: a permutation-based non-parametric analysis of CRISPR screen data; (2) RCRnorm: an integrated system of random-coefficient hierarchical regression models for normalizing NanoString nCounter data from FFPE samples.

Clustered regularly-interspaced short palindromic repeats (CRISPR) screens are usually implemented in cultured cells to identify genes with critical functions. Although several methods have been developed or adapted to analyze CRISPR screening data, no single spe- cific algorithm has gained popularity. Thus, rigorous procedures are needed to overcome the shortcomings of existing algorithms. We developed a Permutation-Based Non-Parametric Analysis (PBNPA) algorithm, which computes p-values at the gene level …

Impact Of Home Field Advantage: Analyzed Across Three Professional Sports, Michael S. Risser, Blake R. Gray, Ryan A. Kelly

Student Publications

We examined the impact of home-field advantage in the NFL, NBA, and MLB. We defined home-field advantage as winning more than 50% of the home games. Additionally, we took into consideration how season length could act as a moderator and influence the impact of home-field advantage. We collected data from the 2015 NBA and MLB seasons and the 2015 and 2016 NFL seasons to determine statistical significance. In total, we got data from 4,141 games to analyze. We found that there is statistical significance that the home team has a better chance of winning than the away team across the …

Introduction To Statistics (Ga Southern), Scott Kersey, Stephen Carden

Mathematics Grants Collections

This Grants Collection for Introduction to Statistics was created under a Round Eight ALG Textbook Transformation Grant.

Affordable Learning Georgia Grants Collections are intended to provide faculty with the frameworks to quickly implement or revise the same materials as a Textbook Transformation Grants team, along with the aims and lessons learned from project teams during the implementation process.

Documents are in .pdf format, with a separate .docx (Word) version available for download. Each collection contains the following materials:

• Linked Syllabus
• Initial Proposal
• Final Report

A Multi-Step Nonlinear Dimension-Reduction Approach With Applications To Bigdata, R. Krishnan, V. A. Samaranayake, Jagannathan Sarangapani

Mathematics and Statistics Faculty Research & Creative Works

In this paper, a multi-step dimension-reduction approach is proposed for addressing nonlinear relationships within attributes. In this work, the attributes in the data are first organized into groups. In each group, the dimensions are reduced via a parametric mapping that takes into account nonlinear relationships. Mapping parameters are estimated using a low rank singular value decomposition (SVD) of distance covariance. Subsequently, the attributes are reorganized into groups based on the magnitude of their respective singular values. The group-wise organization and the subsequent reduction process is performed for multiple steps until a singular value-based user-defined criterion is satisfied. Simulation analysis is …

Understanding Natural Keyboard Typing Using Convolutional Neural Networks On Mobile Sensor Data, Travis Siems

Computer Science and Engineering Theses and Dissertations

Mobile phones and other devices with embedded sensors are becoming increasingly ubiquitous. Audio and motion sensor data may be able to detect information that we did not think possible. Some researchers have created models that can predict computer keyboard typing from a nearby mobile device; however, certain limitations to their experiment setup and methods compelled us to be skeptical of the models’ realistic prediction capability. We investigate the possibility of understanding natural keyboard typing from mobile phones by performing a well-designed data collection experiment that encourages natural typing and interactions. This data collection helps capture realistic vulnerabilities of the security …

College Students’ Personality Traits In Relation To Career Readiness, Shelby R. Overacker, Carly E. Kalis, Francesca Coppola

Student Publications

This study examined sixty-one Gettysburg College juniors and seniors (31 males, 30 females) to measure how the Big Five personality traits, and whether a student has Type D characteristics, determines if a student is career ready. We collected data through an in-person survey, with questions about personality traits, ambition, career readiness, and demographics. Regression was used to statistically analyze our first hypothesis. The results found that there is a significant positive association between conscientiousness and career readiness, but there is no significant association between extraversion and career readiness. For the second hypothesis, a mediation model was used. We found that …

Perceptions Of Transactional And Transformational Leaders According To Gender, Quinn I. Igram, Andrew N. Garstka, Lindsay D. Harris

Student Publications

The lack of females occupying leadership positions in the modern workplace has prompted the research of this study. In order to better understand the perceptions that exist regarding successful leadership, this study was conducted with the intention of understanding individual leadership style through the Multifactor Leadership Questionnaire, which measures transactional and transformational leadership styles (Bass and Avolio, 1993). 64 male and female participants, made up of 36 students and 28 individuals in the workforce ages 18-61 with an average age of 31 answered 21 questions to assess their leadership style and 1 to measure who they perceived as a successful …