Categorical Data Analysis Commons^™

Analysis Of Gameplay Strategies In Hearthstone: A Data Science Approach, Connor W. Watson

Theses

In recent years, games have been a popular test bed for AI research, and the presence of Collectible Card Games (CCGs) in that space is still increasing. One such CCG for both competitive/casual play and AI research is Hearthstone, a two-player adversarial game where players seeks to implement one of several gameplay strategies to defeat their opponent and decrease all of their Health points to zero. Although some open source simulators exist, some of their methodologies for simulated agents create opponents with a relatively low skill level. Using evolutionary algorithms, this thesis seeks to evolve agents with a higher skill …

Decision Tree For Predicting The Party Of Legislators, Afsana Mimi

Publications and Research

The motivation of the project is to identify the legislators who voted frequently against their party in terms of their roll call votes using Office of Clerk U.S. House of Representatives Data Sets collected in 2018 and 2019. We construct a model to predict the parties of legislators based on their votes. The method we used is Decision Tree from Data Mining. Python was used to collect raw data from internet, SAS was used to clean data, and all other calculations and graphical presentations are performed using the R software.

Novel Inference Methods For Generalized Linear Models Using Shrinkage Priors And Data Augmentation., Arinjita Bhattacharyya

Electronic Theses and Dissertations

Generalized linear models have broad applications in biostatistics and sociology. In a regression setup, the main target is to find a relevant set of predictors out of a large collection of covariates. Sparsity is the assumption that only a few of these covariates in a regression setup have a meaningful correlation with an outcome variate of interest. Sparsity is incorporated by regularizing the irrelevant slopes towards zero without changing the relevant predictors and keeping the resulting inferences intact. Frequentist variable selection and sparsity are addressed by popular techniques like Lasso, Elastic Net. Bayesian penalized regression can tackle the curse of …

Preparing For The Future: The Effects Of Financial Literacy On Financial Planning For Young Professionals, Tanay Singh

Senior Theses

Purpose – Many people between the age of 20 and 34 have not considered planning financially for the future in any significant capacity and in doing so, they limit their potential savings. The purpose of this study is to examine what financial expectations are for people in the early stages of their career and determine if improving financial literacy and revealing financial realities helps to produce more accurate or realistic expectations. Ultimately, the goal is to better prepare participants in the study for the working world and increased responsibilities outside of the college/university environment by getting them to start thinking …

Using Alteryx Designer In Audit, Nolan Asiala

Honors Projects

My senior project was built around data analysis and how it relates to the auditing profession. Initially, I was planning on attending a data analytics competition, but that was canceled due to the events of COVID-19. This project utilized the Alteryx Designer program to demonstrate how it can be used during an audit engagement. By creating a workflow in Alteryx Designer, a report from a client can be cleaned and reformatted into a working dataset. My project includes two Excel files, a Microsoft Word document that serves as a brief introduction to the program, and a video describing the workflow …

How Data Is Changing The World Of Healthcare, Cameron Marous

Honors Capstone Enhancement Presentations

No abstract provided.

A Permutation Test And Spatial Cross-Validation Approach To Assess Models Of Interspecific Competition Between Trees, David Allen, Albert Y. Kim

Statistical and Data Sciences: Faculty Publications

Measuring species-specific competitive interactions is key to understanding plant communities. Repeat censused large forest dynamics plots offer an ideal setting to measure these interactions by estimating the species-specific competitive effect on neighboring tree growth. Estimating these interaction values can be difficult, however, because the number of them grows with the square of the number of species. Furthermore, confidence in the estimates can be overestimated if any spatial structure of model errors is not considered. Here we measured these interactions in a forest dynamics plot in a transitional oak-hickory forest. We analytically fit Bayesian linear regression models of annual tree radial …

Evaluation Of Text Mining Techniques Using Twitter Data For Hurricane Disaster Resilience, Joshua Eason, Sathish Kumar

SDSU Data Science Symposium

Data obtained from social media microblogging websites such as Twitter provide the unique ability to collect and analyze conversations of the public in order to gain perspective on the thoughts and feelings of the general public. Sentiment and volume analysis techniques were applied to the dataset in order to gain an understanding of the amount and level of sentiment associated with certain disaster-related tweets, including a topical analysis of specific terms. This study showed that disaster-type events such as a hurricane can cause some strong negative sentiment in the period of time directly preceding the event, but ultimately returns quickly …

Informal Professional Development On Twitter: Exploring The Online Communities Of Mathematics Educators, Jaymie Ruddock

SMU Journal of Undergraduate Research

Professional development in its most traditional form is a classroom setting with a lecturer and an overwhelming amount of information. It is no surprise, then, that informal professional development away from institutions and on the teacher's own terms is a growing phenomenon due to an increased presence of educators on social media. These communities of educators use hashtags to broadcast to each other, with general hashtags such as #edchat having the broadest audience. However, many math educators usethe hashtags #ITeachMath and #MTBoS, communities I was interested in learning more about. I built a python script that used Tweepy to connect …

Mapping Relationships And Positions Of Objects In Images Using Mask And Bounding Box Data, Jaime M. Villanueva Jr, Anantharam Subramanian, Vishal Ahir, Andrew Pollock

SMU Data Science Review

In this paper we present novel methods for automatically annotating images with relationship and position tags that are derived using mask and bounding box data. A Mask Region-based Convolutional Neural Network (Mask R-CNN) is used as the foundation for the ob- ject detection process. The relationships are found by manipulating the bounding box and mask segmentation outputs of a Mask R-CNN. The absolute positions, the positions of the objects relative to the image, and the relative positions, the positions of objects relative to the other objects, are then associated with the images as annotations that are out- put in order …

Wage-Productivity Analysis Of U.S. Domestic Airlines, Jesse Lucas, Khairul Azuar, Justin Tan, Syed Ilyas

Introduction to Research Methods RSCH 202

This study examines the impact of wages on productivity by examining US domestic airlines.

Current literature places emphasis on jobs conducted in-flight, specifically pilots and cabin crew. This paper considers all job titles involved in the operations of the airline, including executives and management. Existing research focuses on factors such as governance, domestic economic level, and personal attributes such as intrinsic motivation, gender, and age. There is insufficient research regarding the relationship between wage and productivity. Thus, it is uncertain if high wage leads to high productivity. Preliminary findings suggest higher wage equates to higher productivity.

Teaching Introductory Statistics With Datacamp, Benjamin Baumer, Andrew P. Bray, Mine Çetinkaya-Rundel, Johanna S. Hardin

Statistical and Data Sciences: Faculty Publications

We designed a sequence of courses for the DataCamp online learning platform that approximates the content of a typical introductory statistics course. We discuss the design and implementation of these courses and illustrate how they can be successfully integrated into a brick-and-mortar class. We reflect on the process of creating content for online consumers, ruminate on the pedagogical considerations we faced, and describe an R package for statistical inference that became a by-product of this development process. We discuss the pros and cons of creating the course sequence and express our view that some aspects were particularly problematic. The issues …

Nonparametric Analysis Of Clustered And Multivariate Data, Yue Cui

Theses and Dissertations--Statistics

In this dissertation, we investigate three distinct but interrelated problems for nonparametric analysis of clustered data and multivariate data in pre-post factorial design.

In the first project, we propose a nonparametric approach for one-sample clustered data in pre-post intervention design. In particular, we consider the situation where for some clusters all members are only observed at either pre or post intervention but not both. This type of clustered data is referred to us as partially complete clustered data. Unlike most of its parametric counterparts, we do not assume specific models for data distributions, intra-cluster dependence structure or variability, in effect …

Inventory Models For Perishable Items Under Markdown Policy, Nurzahara Atika Kamaruzaman

Student Works (2020-2029)

As expected, the demand for a fresh product depends on how fresh it is, therefore, it is important to take expiration date into consideration. Based on marketing and economic theory, several factors such as price, inventory level and advertisement play a crucial role in influencing the demand. Hence, we study the effect of these factors in influencing the demand in the inventory model. Since the demand for perishable product declines over time, markdown policy is offered to increase the demand and profit while reducing the inventory. Salvage value is incorporated to the deteriorating units. In this research, we extend previous …

Inference Of Heterogeneity In Meta-Analysis Of Rare Binary Events And Rss-Structured Cluster Randomized Studies, Chiyu Zhang

Statistical Science Theses and Dissertations

This dissertation contains two topics: (1) A Comparative Study of Statistical Methods for Quantifying and Testing Between-study Heterogeneity in Meta-analysis with Focus on Rare Binary Events; (2) Estimation of Variances in Cluster Randomized Designs Using Ranked Set Sampling.

Meta-analysis, the statistical procedure for combining results from multiple studies, has been widely used in medical research to evaluate intervention efficacy and safety. In many practical situations, the variation of treatment effects among the collected studies, often measured by the heterogeneity parameter, may exist and can greatly affect the inference about effect sizes. Comparative studies have been done for only one or …

Achieving Optimal Horizontal Drill Operations, Daniel J. Serna, James Vasquez, Donald Markley

SMU Data Science Review

In this paper, we present a novel method of predicting the onset of a slide event in horizontal drilling operations. Horizontal drilling operations attempt to create a well through a subsurface as quickly as possible by rotating a drill through the subsurface. A slide event occurs when the drill begins to inefficiently rotate through the subsurface, resulting in a significantly reduced rate of penetration. Slide events can be prevented, or significantly reduced in their impact, when their onset is accurately predicted. We present a method of accurately predicting the onset of slide events with a time-series based predictive model that …

Reduced Bias For Respondent Driven Sampling: Accounting For Non-Uniform Edge Sampling Probabilities In People Who Inject Drugs In Mauritius, Miles Q. Ott, Krista J. Gile, Matthew T. Harrison, Lisa G. Johnston, Joseph W. Hogan

Statistical and Data Sciences: Faculty Publications

People who inject drugs are an important population to study in order to reduce transmission of blood-borne illnesses including HIV and Hepatitis. In this paper we estimate the HIV and Hepatitis C prevalence among people who inject drugs, as well as the proportion of people who inject drugs who are female in Mauritius. Respondent driven sampling (RDS), a widely adopted link-tracing sampling design used to collect samples from hard-to-reach human populations, was used to collect this sample. The random walk approximation underlying many common RDS estimators assumes that each social relation (edge) in the underlying social network has an equal …

Association Of Copy Number Variations With Chronic Hepatitis B In Chinese Population, Fang Niu

Capstone Experience: Master of Public Health

With one third of the Hepatitis B virus (HBV) infection population of the world, chronic Hepatitis B (CHB) has become a top burden in China. CHB is a lifelong infection with HBV which can cause serious health problems, like cirrhosis, liver cancer or even death. HBV infection is known to result in various clinical conditions, including asymptomatic HBV carriers to chronic hepatitis and primary hepatocellular carcinoma. Several studies have shown that host genetic susceptibility could be an important factor that determines these various outcomes of HBV infection. Many Single Nucleotide Polymorphisms (SNPs) and Copy Number Variations (CNVs) have been associated …

Statin Prescription For Patients With Atherosclerotic Cardiovascular Disease From National Survey Data, Kristina Vatcheva, Vicente Aparicio, Ayesha Araya, Eduardo Gonzalez, Susan T. Laing

School of Mathematical & Statistical Sciences Faculty Publications

Despite strong evidence for the use of statins for patients with atherosclerotic cardiovascular disease (ASCVD), statin prescription is still suboptimal. We aimed to determine the rates and factors that influence statin prescription using national survey data. This is a cross-sectional retrospective study on 8,468 patients with clinical ASCVD who were drawn from the National Ambulatory Medical Care Survey and the National Hospital Ambulatory Medical Care Survey from years 2011 to 2015. Survey-weighted analysis was conducted to estimate weighted prevalence and odds ratios for statin prescription. There was a significant increase in statin prescription from the years 2011 to 2015. Nevertheless, …

Field Drilling Data Cleaning And Preparation For Data Analytics Applications, Daniel Cardoso Braga

LSU Master's Theses

Throughout the history of oil well drilling, service providers have been continuously striving to improve performance and reduce total drilling costs to operating companies. Despite constant improvement in tools, products, and processes, data science has not played a large part in oil well drilling. With the implementation of data science in the energy sector, companies have come to see significant value in efficiently processing the massive amounts of data produced by the multitude of internet of thing (IOT) sensors at the rig. The scope of this project is to combine academia and industry experience to analyze data from 13 different …