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Full-Text Articles in Statistics and Probability

Hot Hands Or Chance Happenings? A Simulation-Based Approach For Wnba Teams, Ruben Jimenez Jun 2026

Hot Hands Or Chance Happenings? A Simulation-Based Approach For Wnba Teams, Ruben Jimenez

Master's Theses

The hot hand is a polarizing topic in basketball analytics: fans, stakeholders, and even players themselves assert confidently their belief or disbelief in the idea that players who perform well will continue to do so over an extended period of time. Statistical research has been conducted since as early as 1985 to attempt to disprove or prove the existence of this phenomenon. More recent works have refuted the earliest objections to the hot hand’s existence, with conclusions aided by robust simulation techniques. In this work, we compare hypothesis tests using multiple simulation techniques to explore the hot hand at the …


Designing The Protocol For An Experimental Flight Simulation Study Encouraging Fuel Efficient Behavior, Thomas S. Reardon Sep 2025

Designing The Protocol For An Experimental Flight Simulation Study Encouraging Fuel Efficient Behavior, Thomas S. Reardon

Theses and Dissertations

This study designed and tested an experimental instrument to examine how pilots respond to fuel efficiency feedback in a flight simulator. A standardized flight plan, script, and hardware setup were created using X-Plane 12 software and physical flight simulator hardware. The chosen sortie guided participants from Monterey Regional Airport to Moffett Federal Airfield using instrument flight rules (IFR). The flight script provided step-by-step guidance to ensure consistent behavior across participants. The simulator was mapped to match real cockpit controls and allowed for precise data collection including flight time, altitude, heading, and fuel use. The goal was to support a larger …


Nba Player Types And Salaries: Assessing The Disparities In Pay, Nick Riccardi, Rodney J. Paul Aug 2025

Nba Player Types And Salaries: Assessing The Disparities In Pay, Nick Riccardi, Rodney J. Paul

Sport Management - All Scholarship

The purpose of this study was to identify player types that exist in the modern National Basketball Association (NBA), test whether player types are paid differently controlling for performance and other factors and construct successful rosters with cheaper payrolls.
We collected performance statistics and salary data for players and teams across five seasons (2018-19 to 2022-23). Cluster analysis is leveraged to group together player-seasons to identify the player types that exist in the NBA. Linear regression models are run to test for differences in pay by cluster membership while controlling for performance, age, and contractual details. Linear programming simulation models …


Quantifying The Sensitivity Of Land Use Land Cover Metrics Through Simulation Techniques, Haley Burger Aug 2025

Quantifying The Sensitivity Of Land Use Land Cover Metrics Through Simulation Techniques, Haley Burger

All Graduate Theses and Dissertations, Fall 2023 to Present

As human activities and climate change continue to reshape our landscape, understanding how land use changes over time is becoming increasingly important. Accurate ways to track and analyze these changes are essential for governments, businesses, and communities to make informed decisions. Monitoring agricultural land is particularly critical, as shifts in land use can impact food production and environmental pollutants. One of the primary tools used in the United States to monitor agricultural land is the Cropland Data Layer (CDL), an annual map created by the United States Department of Agriculture (USDA) from satellite images. While the CDL is highly accurate, …


Statistical Investigations Of Strategies In The Game Ecosystem, Dylan Li Jun 2025

Statistical Investigations Of Strategies In The Game Ecosystem, Dylan Li

Master's Theses

This work provides a probability-based analysis of strategies in the board game Ecosystem. Ecosystem is a turn-based multiplayer tiling game, where players take turns picking a wildlife card from a limited pool of cards then placing that card on their personal 4x5 grid. The objective of the game is to place the wildlife cards to maximize your score, as each card’s scoring condition depends on the presence or absence of certain cards surrounding it. The goal of this project is to determine optimal strategies for tiling your grid using techniques such as simulation to find optimal grid arrangements and clustering …


Theory And Applications Surrounding Markov Chains, Joseph J. Quisito Jr., Gallean Brown, Elijah Yoder Jan 2025

Theory And Applications Surrounding Markov Chains, Joseph J. Quisito Jr., Gallean Brown, Elijah Yoder

Capstone Showcase

This capstone project explores the Markov Chain – a mathematical model used to describe systems that transition between states based on probabilities. It begins by introducing the fundamental concepts, including transition matrices, state classifications, and stationary distributions. The paper then applies Markov Chain theory to real-world scenarios, such as simulating Snakes and Ladders games, predicting soccer match outcomes for Manchester United, and generating texts from movie lines. Finally, it discusses key findings, challenges, and potential areas for future research in the field.


Linking Empirical Data And Numerical Simulation To Characterize Dynamic Fire Behavior Associated With Interacting Firelines, Marta Sergeevna Jerebets Jan 2025

Linking Empirical Data And Numerical Simulation To Characterize Dynamic Fire Behavior Associated With Interacting Firelines, Marta Sergeevna Jerebets

Graduate Student Theses, Dissertations, & Professional Papers

Understanding fuel pattern-fire process relationships is key for predicting fire behavior and effects with follow-on benefits to proactive fire management and model validation. To characterize dynamic fire behavior, this thesis leverages empirical data and numerical simulation through two complementary studies.

In the first study, longwave thermal sensors aboard unmanned aerial systems (UAS) were used to capture fine-scale fire behavior in two experimental grass burns. A novel paired design was used to quantify the effects of fuel arrangement on fire behavior with 3.66 m diameter treatments cut to a height of 0.15 m. The treatments ephemerally reduced fire rate of spread …


Mean From Median Estimation In Longitudinal Meta-Analysis Of Quality Of Life In Radiation Oncology Patients, Harlan R. Sayles Dec 2024

Mean From Median Estimation In Longitudinal Meta-Analysis Of Quality Of Life In Radiation Oncology Patients, Harlan R. Sayles

Theses & Dissertations

Meta-analysis of longitudinal data, where some of the studies report results with means and standard errors while others use medians and ranges, is a complex analytical problem with several challenges which must be overcome. Existing methods for estimating means from medians and either ranges, interquartile ranges, or both have not previously been evaluated in a longitudinal setting. In this work, a simulation study was used to estimate mean bias, between studies variance bias, and coverage of confidence intervals in a longitudinal setting. A second simulation study estimated the variance of meta-analysis results from a given set of studies that may …


Cluster Effect For Snp-Snp Interaction Pairs For Predicting Complex Traits, Hui Yi Lin, Harun Mazumder, Indrani Sarkar, Po Yu Huang, Rosalind A. Eeles, Zsofia Kote-Jarai, Kenneth R. Muir, Johanna Schleutker, Nora Pashayan, Jyotsna Batra, David E. Neal, Sune F. Nielsen, Børge G. Nordestgaard, Henrik Grönberg, Fredrik Wiklund, Robert J. Macinnis, Christopher A. Haiman, Ruth C. Travis, Janet L. Stanford, Adam S. Kibel, Cezary Cybulski, Kay Tee Khaw, Christiane Maier, Stephen N. Thibodeau, Manuel R. Teixeira, Lisa Cannon-Albright, Hermann Brenner, Radka Kaneva, Hardev Pandha, Et Al Aug 2024

Cluster Effect For Snp-Snp Interaction Pairs For Predicting Complex Traits, Hui Yi Lin, Harun Mazumder, Indrani Sarkar, Po Yu Huang, Rosalind A. Eeles, Zsofia Kote-Jarai, Kenneth R. Muir, Johanna Schleutker, Nora Pashayan, Jyotsna Batra, David E. Neal, Sune F. Nielsen, Børge G. Nordestgaard, Henrik Grönberg, Fredrik Wiklund, Robert J. Macinnis, Christopher A. Haiman, Ruth C. Travis, Janet L. Stanford, Adam S. Kibel, Cezary Cybulski, Kay Tee Khaw, Christiane Maier, Stephen N. Thibodeau, Manuel R. Teixeira, Lisa Cannon-Albright, Hermann Brenner, Radka Kaneva, Hardev Pandha, Et Al

School of Public Health Faculty Publications

Single nucleotide polymorphism (SNP) interactions are the key to improving polygenic risk scores. Previous studies reported several significant SNP-SNP interaction pairs that shared a common SNP to form a cluster, but some identified pairs might be false positives. This study aims to identify factors associated with the cluster effect of false positivity and develop strategies to enhance the accuracy of SNP-SNP interactions. The results showed the cluster effect is a major cause of false-positive findings of SNP-SNP interactions. This cluster effect is due to high correlations between a causal pair and null pairs in a cluster. The clusters with a …


The Impact Of “Multiple Looks” When Performing Survival Analysis, Quentin Eloise Aug 2024

The Impact Of “Multiple Looks” When Performing Survival Analysis, Quentin Eloise

Electronic Theses and Dissertations

Survival analysis is a critical statistical method in healthcare to assess patient treatment effects and disease progression. Another critical area of statistical methodology in health care is the practice of adaptive designs. Adaptive designs allow for interim analyses to take place during a study and various decisions and actions can take place more ethically. This is beneficial for studies that take multiple years to complete and allows administrators and healthcare providers to make sound decisions as early as possible. A challenging aspect of adaptive designs is that the number of interim analyses is known in advance which is applicable in …


Simulation Study On Confidence Interval Estimation For Standard Deviation With Non-Normal Distributions, Theophilus Oppong Kyeremeh Aug 2024

Simulation Study On Confidence Interval Estimation For Standard Deviation With Non-Normal Distributions, Theophilus Oppong Kyeremeh

Electronic Theses and Dissertations

This study explores innovative approaches to constructing confidence intervals for the population standard deviation, σ, in non-normal data scenarios. While the sample standard deviation, s, is widely used, its reliability is compromised when dealing with skewed or heavy-tailed distributions and exhibits sensitivity to outliers. Our research addresses these limitations by investigating alternative estimation methods that offer greater robustness and accuracy.


Value Added Tax Rate Variation, Import Demand And Sectoral Output In Nigeria, Joshua K. Nomkuha, Aondoawase Asooso, Philip T. Abachi Jun 2024

Value Added Tax Rate Variation, Import Demand And Sectoral Output In Nigeria, Joshua K. Nomkuha, Aondoawase Asooso, Philip T. Abachi

CBN Journal of Applied Statistics (JAS)

This study employs computable general equilibrium (CGE) model to estimate the effect of increase in value added tax (VAT), from 5 per cent to 7.5 per cent, on import demand and sectoral output in Nigeria. The study uses 2020 as the base year for the data analysis. The results show that increase in VAT affects import demand negatively, based on import penetration ratios, with mixed effect across six sectors. The implication of the result is that the VAT policy discourage consumption of foreign products, and constitute excess burden to consumers of such products in Nigeria. The results further reveal that …


Stock Market Volatility In The United Kingdom: Simulating Post-Covid-19 Recovery, Bala A. Dahiru, Mohammed Shuaibu, Najibullah Hassanov Jun 2024

Stock Market Volatility In The United Kingdom: Simulating Post-Covid-19 Recovery, Bala A. Dahiru, Mohammed Shuaibu, Najibullah Hassanov

CBN Journal of Applied Statistics (JAS)

This paper investigates the time it would take for the FTSE-100 index to reach its post-COVID-19 peak. The paper utilises an exponential generalised autoregressive conditional heteroscedasticity (EGARCH) model that accounts for leverage effect and asymmetries. The preferred models amongst competing variants was the Autoregressive Moving Average (ARMA)-EGARCH(2,1) specification and was used to predict daily FTSE-100 data from 5th January 2000 to 21st June 2024. The empirical exercise showed that the COVID-19-induced financial crisis negatively affected the United Kingdom’s stock market performance. The results show that the FTSE100 index could reach its post-pandemic peak around 27th August, 2024 (two months after …


Qwixx Strategies Using Simulation And Mcmc Methods, Joshua W. Blank Jun 2024

Qwixx Strategies Using Simulation And Mcmc Methods, Joshua W. Blank

Master's Theses

This study explores optimal strategies for maximizing scores and winning in the popular dice game Qwixx, analyzing both single and multiplayer gameplay scenarios. Through extensive simulations, various strategies were tested and compared, including a scorebased approach that uses a formula tuned by MCMC random walks, and race-to-lock approaches which use absorbing Markov chain qualities of individual score sheet rows to find ways to lock rows as quickly as possible. Results indicate that employing a scorebased strategy, considering gap, count, position, skip, and likelihood scores, significantly improves performance in single player games, while move restrictions based on specific dice roll sums …


Comparing North American Professional Sports League Season Formats Using Monte Carlo Simulation, Lathan Gregg May 2024

Comparing North American Professional Sports League Season Formats Using Monte Carlo Simulation, Lathan Gregg

Industrial Engineering Undergraduate Honors Theses

Each NFL, NBA, and MLB season consists of a regular season, in which teams play a set number of scheduled games and a playoff, in which qualifying teams compete for a championship. At the conclusion of each season, teams are ranked based on their performance throughout the season. This study aims to investigate the ability of each league's season format to accurately rank teams using Monte Carlo simulation. Matches between two teams are simulated by using the team’s assigned strength ranks to calculate a winning probability for each team. The winning probabilities are simulated with different skill values, dictating how …


Deterministic Global 3d Fractal Cloud Model For Synthetic Scene Generation, Aaron M. Schinder, Shannon R. Young, Bryan J. Steward, Michael L. Dexter, Andrew Kondrath, Stephen Hinton, Ricardo Davila May 2024

Deterministic Global 3d Fractal Cloud Model For Synthetic Scene Generation, Aaron M. Schinder, Shannon R. Young, Bryan J. Steward, Michael L. Dexter, Andrew Kondrath, Stephen Hinton, Ricardo Davila

Faculty Publications

This paper describes the creation of a fast, deterministic, 3D fractal cloud renderer for the AFIT Sensor and Scene Emulation Tool (ASSET). The renderer generates 3D clouds by ray marching through a volume and sampling the level-set of a fractal function. The fractal function is distorted by a displacement map, which is generated using horizontal wind data from a Global Forecast System (GFS) weather file. The vertical windspeed and relative humidity are used to mask the creation of clouds to match realistic large-scale weather patterns over the Earth. Small-scale detail is provided by the fractal functions which are tuned to …


Establishing Practical Equivalence Of Factor Loadings In Multigroup Confirmatory Factor Analysis, Christopher Edward Shank Apr 2024

Establishing Practical Equivalence Of Factor Loadings In Multigroup Confirmatory Factor Analysis, Christopher Edward Shank

Dissertations

This dissertation compares the performance of equivalence test (EQT) and null hypothesis test (NHT) procedures for identifying invariant and noninvariant factor loadings under a range of experimental manipulations. EQT is the statistically appropriate approach when the research goal is to find evidence of group similarity rather than group difference; despite this, the conventional approach to measurement invariance analysis relies upon NHT. EQT has proved effective for invariance detection using global model-data fit statistics in simulated and real-world data (Counsell et al., 2020) but its use in partial measurement invariance (PMI) analysis for evaluation of factor loading differences between groups has …


Generating Neutrosophic Random Variables Based Gamma Distribution, Maissam Ahmad Jdid, Florentin Smarandache, Khalifa Al Shaqsi Jan 2024

Generating Neutrosophic Random Variables Based Gamma Distribution, Maissam Ahmad Jdid, Florentin Smarandache, Khalifa Al Shaqsi

Branch Mathematics and Statistics Faculty and Staff Publications

In practical life, we encounter many systems that cannot be studied directly, either due to their high cost or because some of these systems cannot be studied directly. Therefore, we resort to the simulation method, which depends on applying the study to systems similar to real ones and then projecting these results if they are suitable for the real system. The simulation process requires a good understanding of probability distributions and the methods used to transform random numbers that follow a regular distribution in the field [0,1] into random variables that follow them, so that we can achieve the greatest …


A New Method To Determine The Posterior Distribution Of Coefficient Alpha, John Mart V. Delosreyes Oct 2023

A New Method To Determine The Posterior Distribution Of Coefficient Alpha, John Mart V. Delosreyes

Psychology Theses & Dissertations

There is a focus within the behavioral/social sciences on non-physical, psychological constructs (i.e., constructs). These constructs are indirectly measured using measurement instruments that consist of questions that capture the manifestations of these constructs. The indirect nature of measuring constructs results in a need of ensuring that measurement instruments are reliable. The most popular statistic used to estimate reliability is coefficient alpha as it is easy to compute and has properties that make it desirable to use. Coefficient alpha’s popularity has resulted in a wide breadth of research into its qualities. Notably, research about coefficient alpha’s distribution has led to developments …


Uconn Baseball Batting Order Optimization, Gavin Rublewski, Gavin Rublewski May 2023

Uconn Baseball Batting Order Optimization, Gavin Rublewski, Gavin Rublewski

Honors Scholar Theses

Challenging conventional wisdom is at the very core of baseball analytics. Using data and statistical analysis, the sets of rules by which coaches make decisions can be justified, or possibly refuted. One of those sets of rules relates to the construction of a batting order. Through data collection, data adjustment, the construction of a baseball simulator, and the use of a Monte Carlo Simulation, I have assessed thousands of possible batting orders to determine the roster-specific strategies that lead to optimal run production for the 2023 UConn baseball team. This paper details a repeatable process in which basic player statistics …


Statistical Approach To Quantifying Interceptability Of Interaction Scenarios For Testing Autonomous Surface Vessels, Benjamin E. Hargis, Yiannis E. Papelis Apr 2023

Statistical Approach To Quantifying Interceptability Of Interaction Scenarios For Testing Autonomous Surface Vessels, Benjamin E. Hargis, Yiannis E. Papelis

Modeling, Simulation and Visualization Student Capstone Conference

This paper presents a probabilistic approach to quantifying interceptability of an interaction scenario designed to test collision avoidance of autonomous navigation algorithms. Interceptability is one of many measures to determine the complexity or difficulty of an interaction scenario. This approach uses a combined probability model of capability and intent to create a predicted position probability map for the system under test. Then, intercept-ability is quantified by determining the overlap between the system under test probability map and the intruder’s capability model. The approach is general; however, a demonstration is provided using kinematic capability models and an odometry-based intent model.


Stochastic Optimization To Reduce Aircraft Taxi-In Time At Igia, New Delhi, Rajib Das, Saileswar Ghosh, Rajendra Desai, Pijus Kanti Bhuin, Stuti Agarwal Jan 2023

Stochastic Optimization To Reduce Aircraft Taxi-In Time At Igia, New Delhi, Rajib Das, Saileswar Ghosh, Rajendra Desai, Pijus Kanti Bhuin, Stuti Agarwal

International Journal of Aviation, Aeronautics, and Aerospace

Since there is an uncertainty in the arrival times of flights, pre-scheduled allocation of runways and stands and the subsequent first-come-first-served treatment results in a sub-optimal allocation of runways and stands, this is the prime reason for the unusual delays in taxi-in times at IGIA, New Delhi.

We simulated the arrival pattern of aircraft and utilized stochastic optimization to arrive at the best runway-stands allocation for a day. Optimization is done using a GRG Non-Linear algorithm in the Frontline Systems Analytic Solver platform. We applied this model to eight representative scenarios of two different days. Our results show that without …


Statistical Models For Decision-Making In Professional Soccer, Sean Hellingman Jan 2023

Statistical Models For Decision-Making In Professional Soccer, Sean Hellingman

Theses and Dissertations (Comprehensive)

As soccer is widely regarded as the most popular sport in the world there is high interest in methods of improving team performances. There are many ways teams and individual athletes can influence their own performances during competition. This thesis focuses on developing statistical methodologies for improving competition-based decision-making for soccer so as to allow professional soccer teams to make better informed decisions regarding player selection and in-game decision-making.

To properly capture the dynamic actions of professional soccer, Markov chains with increasing complexity are proposed. These models allow for the inclusion of potential changes in the process caused by goals …


Machine Learning Model Comparison And Arma Simulation Of Exhaled Breath Signals Classifying Covid-19 Patients, Aaron Christopher Segura Aug 2022

Machine Learning Model Comparison And Arma Simulation Of Exhaled Breath Signals Classifying Covid-19 Patients, Aaron Christopher Segura

Mathematics & Statistics ETDs

This study compared the performance of machine learning models in classifying COVID-19 patients using exhaled breath signals and simulated datasets. Ground truth classification was determined by the gold standard Polymerase Chain Reaction (PCR) test results. A residual bootstrapped method generated the simulated datasets by fitting signal data to Autoregressive Moving Average (ARMA) models. Classification models included neural networks, k-nearest neighbors, naïve Bayes, random forest, and support vector machines. A Recursive Feature Elimination (RFE) study was performed to determine if reducing signal features would improve the classification models performance using Gini Importance scoring for the two classes. The top 25% of …


Bidirectional Testing For Repairable Systems Reliability: Power Asymmetries, Panel Of Control Charts, And Reliability Graphics, Sung Keun Koo Aug 2022

Bidirectional Testing For Repairable Systems Reliability: Power Asymmetries, Panel Of Control Charts, And Reliability Graphics, Sung Keun Koo

UNLV Theses, Dissertations, Professional Papers, and Capstones

To a practitioner who chooses to be on the safe side, we offer an option between a cocktail of tests and a solo one-size-fits-all test as a needed antidote to power asymmetries. Two bidirectional tests are first established to empower a basic pair of tests as asymmetrical performances. Unsurprisingly, we’ve seen either bidirectional device championing in one alternative setting, but also being turned against the very setting altered with just one of the composed elements. Progressing by filtering out the bad and enhancing the good, we assemble a hybrid from the empowered pair to restore power symmetries that are thought …


(R1239) A New Type Ii Half Logistic-G Family Of Distributions With Properties, Regression Models, System Reliability And Applications, Emrah Altun, Morad Alizadeh, Haitham M. Yousof, Mahdi Rasekhi, G. G. Hamedani Dec 2021

(R1239) A New Type Ii Half Logistic-G Family Of Distributions With Properties, Regression Models, System Reliability And Applications, Emrah Altun, Morad Alizadeh, Haitham M. Yousof, Mahdi Rasekhi, G. G. Hamedani

Applications and Applied Mathematics: An International Journal (AAM)

This study proposes a new family of distributions based on the half logistic distribution. With the new family, the baseline distributions gain flexibility through additional shape parameters. The important statistical properties of the proposed family are derived. A new generalization of the Weibull distribution is used to introduce a location-scale regression model for the censored response variable. The utility of the introduced models is demonstrated in survival analysis and estimation of the system reliability. Three data sets are analyzed. According to the empirical results, it is observed that the proposed family gives better results than other existing models.


Applications And Power Analyzation Of New Multiple Testing Procedures Based On Covering Principle, Yu Zhang Nov 2021

Applications And Power Analyzation Of New Multiple Testing Procedures Based On Covering Principle, Yu Zhang

Student Theses and Dissertations

Multiple comparison tests are quite prevalent in clinical trials to increase efficiency and the chance of finding treatment or drug effects. However, making multiple comparisons will lead to the potential inflation of the Type I error rate. How well one test procedure controls the rate of false-positive conclusions becomes the main concern nowadays. A novel method named Covering Principle has been proposed recently. It provides a new approach to designing multiple testing procedures from the angle of rejection regions in the sample space, rather than in the parameter space, which uses in the methods based on the closed testing and …


Applying Deep Learning To The Ice Cream Vendor Problem: An Extension Of The Newsvendor Problem, Gaffar Solihu Aug 2021

Applying Deep Learning To The Ice Cream Vendor Problem: An Extension Of The Newsvendor Problem, Gaffar Solihu

Electronic Theses and Dissertations

The Newsvendor problem is a classical supply chain problem used to develop strategies for inventory optimization. The goal of the newsvendor problem is to predict the optimal order quantity of a product to meet an uncertain demand in the future, given that the demand distribution itself is known. The Ice Cream Vendor Problem extends the classical newsvendor problem to an uncertain demand with unknown distribution, albeit a distribution that is known to depend on exogenous features. The goal is thus to estimate the order quantity that minimizes the total cost when demand does not follow any known statistical distribution. The …


Jmasm 57: Bayesian Survival Analysis Of Lomax Family Models With Stan (R), Mohammed H. A. Abujarad, Athar Ali Khan Jun 2021

Jmasm 57: Bayesian Survival Analysis Of Lomax Family Models With Stan (R), Mohammed H. A. Abujarad, Athar Ali Khan

Journal of Modern Applied Statistical Methods

An attempt is made to fit three distributions, the Lomax, exponential Lomax, and Weibull Lomax to implement Bayesian methods to analyze Myeloma patients using Stan. This model is applied to a real survival censored data so that all the concepts and computations will be around the same data. A code was developed and improved to implement censored mechanism throughout using rstan. Furthermore, parallel simulation tools are also implemented with an extensive use of rstan.


Observational Studies In Group Testing And Potential Applications., Alexander Christopher Noll May 2021

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 …