Applied Statistics Commons^™

Evaluating Soil Health Changes Following Cover Crop And No-Till Integration Into A Soybean (Glycine Max) Cropping System In The Mississippi Alluvial Valley, Alexandra Gwin Firth

Theses and Dissertations

The transition of natural landscapes to intensive agricultural uses has resulted in severe loss of soil organic carbon (SOC), increased CO₂ emissions, river depletion, and groundwater overdraft. Despite negative documented effects of agricultural land use (i.e., soil erosion, nutrient runoff) on critical natural resources (i.e., water, soil), food production must increase to meet the demands of a rising human population. Given the environmental and agricultural productivity concerns of intensely managed soils, it is critical to implement conservation practices that mitigate the negative effects of crop production and enhance environmental integrity. In the Mississippi Alluvial Valley (MAV) region of Mississippi, USA, …

Impact Of Climate Oscillations/Indices On Hydrological Variables In The Mississippi River Valley Alluvial Aquifer., Meena Raju

Theses and Dissertations

The Mississippi River Valley Alluvial Aquifer (MRVAA) is one of the most productive agricultural regions in the United States. The main objectives of this research are to identify long term trends and change points in hydrological variables (streamflow and rainfall), to assess the relationship between hydrological variables, and to evaluate the influence of global climate indices on hydrological variables. Non-parametric tests, MMK and Pettitt’s tests were used to analyze trend and change points. PCC and Streamflow elasticity analysis were used to analyze the relationship between streamflow and rainfall and the sensitivity of streamflow to rainfall changes. PCC and MLR analysis …

A Two-Layer Model Explains Higher-Order Feature Selectivity Of V2 Neurons, Timothy D. Oleskiw, Justin D. Lieber, J. Anthony Movshon, Eero P. Simoncelli

MODVIS Workshop

Neurons in cortical area V2 respond selectively to higher-order visual features, such as the quasi-periodic structure of natural texture. However, a functional account of how V2 neurons build selectivity for complex natural image features from their inputs – V1 neurons locally tuned for orientation and spatial frequency – remains elusive.

We made single-unit recordings in area V2 in two fixating rhesus macaques. We presented stimuli composed of multiple superimposed grating patches that localize contrast energy in space, orientation, and scale. V2 activity is modeled via a two-layer linear-nonlinear network, optimized to use a sparse combination of V1-like outputs to account …

Generating A Dataset For Comparing Linear Vs. Non-Linear Prediction Methods In Education Research, Jack Mauro, Elena Martinez, Anna Bargagliotti

Honors Thesis

Machine learning is often used to build predictive models by extracting patterns from large data sets. Such techniques are increasingly being utilized to predict outcomes in the social sciences. One such application is predicting student success. Machine learning can be applied to predicting student acceptance and success in academia. Using these tools for education-related data analysis, may enable the evaluation of programs, resources and curriculum. Currently, research is needed to examine application, admissions, and retention data in order to address equity in college computer science programs. However, most student-level data sets contain sensitive data that cannot be made public. To …

Understanding And Improving The System: The Effects Of Weighting On The Accuracy Of Political Polling In Arkansas, Beck Williams

Political Science Undergraduate Honors Theses

In an effort to increase the accuracy of statewide political polling in Arkansas, we explore the statistical strategy of weighting with a focus on one yearly opinion poll: The Arkansas Poll. We conduct over 70 weighting experiments on the 2016 and 2020 Arkansas Polls using a variety of variables and opinion questions. From these experiments, we find that while some weighted variables tend to create larger changes, weighting typically results in a single-digit percentage change that does not substantially shift or “flip” the majorities. Due to a greater rate of change through weighting in the 2020 Poll compared to the …

Sensory Comparison Of Beer Carbonated Using Forced Carbonation And The Carbo Rock-It, Michala Smith

Biological and Agricultural Engineering Undergraduate Honors Theses

Craft brewing is a growing market which represents over 12% of beer produced in the United States. Dr. G Scott Osborn, PE invented the Carbo Rock-It™ to improve the carbonation process for craft breweries. The invention allows for shorter carbonation time and uses less CO₂, saving companies money and time. Because of the lack of gas losses through bubbling, Osborn theorized that the Carbo Rock-It could also prevent the “stripping of the nose” that can occur in traditional forced carbonation. Existing research supports the mechanism, as beer flavor and aroma volatiles have been detected during the release of …

Attempting To Predict The Unpredictable: March Madness, Coleton Kanzmeier

Theses/Capstones/Creative Projects

Each year, millions upon millions of individuals fill out at least one if not hundreds of March Madness brackets. People test their luck every year, whether for fun, with friends or family, or to even win some money. Some people rely on their basketball knowledge whereas others know it is called March Madness for a reason and take a shot in the dark. Others have even tried using statistics to give them an edge. I intend to follow a similar approach, using statistics to my advantage. The end goal is to predict this year’s, 2022, March Madness bracket. To achieve …

Intraday Algorithmic Trading Using Momentum And Long Short-Term Memory Network Strategies, Andrew R. Whitinger Ii

Undergraduate Honors Theses

Intraday stock trading is an infamously difficult and risky strategy. Momentum and reversal strategies and long short-term memory (LSTM) neural networks have been shown to be effective for selecting stocks to buy and sell over time periods of multiple days. To explore whether these strategies can be effective for intraday trading, their implementations were simulated using intraday price data for stocks in the S&P 500 index, collected at 1-second intervals between February 11, 2021 and March 9, 2021 inclusive. The study tested 160 variations of momentum and reversal strategies for profitability in long, short, and market-neutral portfolios, totaling 480 portfolios. …

Finding A Representative Distribution For The Tail Index Alpha, Α, For Stock Return Data From The New York Stock Exchange, Jett Burns

Electronic Theses and Dissertations

Statistical inference is a tool for creating models that can accurately display real-world events. Special importance is given to the financial methods that model risk and large price movements. A parameter that describes tail heaviness, and risk overall, is α. This research finds a representative distribution that models α. The absolute value of standardized stock returns from the Center for Research on Security Prices are used in this research. The inference is performed using R. Approximations for α are found using the ptsuite package. The GAMLSS package employs maximum likelihood estimation to estimate distribution parameters using the CRSP data. The …

Groundwork For The Development Of Gpu Enabled Group Testing Regression Models, Paul Cubre

All Dissertations

In this dissertation, we develop novel techniques that allow for the regression analysis of data emerging from group testing processes and set the groundwork for graphic processing units (GPU) enabled implementations. Group testing primarily occurs in clinical laboratories, where it is used to quickly and cheaply diagnose patients. Typically, group testing tests a pooled specimen--several specimens combined into one sample--instead of testing individual specimens one-by-one. This method reduces costs by using fewer tests when the disease prevalence is low. Due to recent advances in diagnostic technology, group testing protocols were extended to incorporate multiplex assays, which are diagnostic tests that, …

Posterior Predictive Model Checking Of The Hierarchical Rater Model, Nnamdi Chika Ezike

Graduate Theses and Dissertations

Fitting wrongly specified models to observed data may lead to invalid inferences about the model parameters of interest. The current study investigated the performance of the posterior predictive model checking (PPMC) approach in detecting model-data misfit of the hierarchical rater model (HRM). The HRM is a rater-mediated model that incorporates components of the polytomous item response theory (IRT) model, such as the partial credit model (PCM) and generalized partial credit model (GPCM), at the second level of the hierarchy, to model examinees’ responses to performance assessments. To date, the HRM has not been rigorously evaluated using PPMC techniques. Monte Carlo …

A Contribution To The Statistical Analysis Of Climate-Wildfire Interaction In Northern California, Adam Diaz

All Theses

Wildfires are extreme weather events that exist at the interface of atmospheric, ecological, and human processes. Ongoing anthropogenic climate change is expected to impact the distribution, frequency, and behavior of wildfires on a grand scale, however the exact nature of this change remains shrouded in a great deal of uncertainty. This study takes a statistical approach to the question over the fire-prone Northern California region of the western United states. Climate model projections are analyzed to investigate changes in a major driver of fire weather in the region. The relationship between wildfire severity and climate factors is then explored separately, …

To Adopt Blockchain Technology Or Not: Is The Decision-Making Process Immune To Covid-19?, Rebecca Jauch

Thinking Matters Symposium

Blockchain technology has been shown to have advantages in improving the effectiveness of supply chain management. We use the Technology-Organization-Environment (TOE) framework with Threat-Rigidity Theory (TRT) to determine the factors that lead U.S. businesses to adopt blockchain technology, the factors that act as barriers to adoption, and the disruptive effect of COVID-19 on the rate of blockchain adoption

The Biggest Loser: How Tanking In Professional Sports Impacts Fan Perception, Julia Ayres

Honors Projects in Mathematics

Professional sports teams are adored nationwide for their talents and the pride they bring to their city for their efforts. However, not all teams take this responsibility seriously and will lose on purpose, or tank, to gain a higher draft pick in the future. Although the long-term goals of tanking are to help the organization, many people take issue with athletes not putting in their best efforts in every game. Teams in both the NBA and NFL are guilty of tanking to gain better draft picks but not all have found success in this process. This leads to important questions …

Percentage Of Yellow Sour Patch Kids, Easton Kratzer, Sarah Baxter

Harrisburg University Research Symposium: Highlighting Research, Innovation, & Creativity

After being given the Qualitative Research Project in Introduction to Statistics, I came up with the question asking what percentage of Sour Patch Kids are yellow. This resulted in me going through an entire bag and counting the amount of every color to figure out the percentages. (Class Project)

A Statistical Study Of Operating Systems At Harrisburg University, Dylan Morgan, Ethan Collins, Joshua Moody, Akeisha Belgrave

Harrisburg University Research Symposium: Highlighting Research, Innovation, & Creativity

We conducted a survey of 100 students to find out which operating system students are using for their main school laptop. (Class Project)

Preference For Violence By Gender, Ayrton Hall, Christian Watson, Akeisha Belgrave

Harrisburg University Research Symposium: Highlighting Research, Innovation, & Creativity

In our survey we asked students of HU what their favorite video games were as well as their favorite genre and most played game. We then analyzed the data to see how gender affects preference for violent games. (Class Project)

Favorite Programming Language Among Students, Anwar Jawhar, Akeisha Belgrave

Harrisburg University Research Symposium: Highlighting Research, Innovation, & Creativity

This project involves understanding the favorite programming language among students. I hypothesize that the favorite programming language will be Python. (Class Project)

A Statistical Study Into The Relationship Between The Student Age And Their Academic Performance, Umangkumar Patel, Akeisha Belgrave

Harrisburg University Research Symposium: Highlighting Research, Innovation, & Creativity

This project will conduct a research in order to find out the relationship between the age of a student and their academic performance. This project will survey at least 100 students. (Class Project)

Intra-Hour Solar Forecasting Using Cloud Dynamics Features Extracted From Ground-Based Infrared Sky Images, Guillermo Terrén-Serrano

Electrical and Computer Engineering ETDs

Due to the increasing use of photovoltaic systems, power grids are vulnerable to the projection of shadows from moving clouds. An intra-hour solar forecast provides power grids with the capability of automatically controlling the dispatch of energy, reducing the additional cost for a guaranteed, reliable supply of energy (i.e., energy storage). This dissertation introduces a novel sky imager consisting of a long-wave radiometric infrared camera and a visible light camera with a fisheye lens. The imager is mounted on a solar tracker to maintain the Sun in the center of the images throughout the day, reducing the scattering effect produced …