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Simplicity As A New Environmental Virtue, Justin Wheeler 2020 Utah State University

Simplicity As A New Environmental Virtue, Justin Wheeler

Undergraduate Honors Capstone Projects

This paper argues for the addition of a new environmentally focused virtue, simplicity, to the virtue ethical framework developed by Aristotle. First, relevant background from Aristotle’s virtue ethics are developed including the crucial, “doctrine of the mean”, a balance between excess and deficiency of a specified character trait. The tenets of the new virtue simplicity are developed with practical examples based on Aristotle’s method of developing a virtue of character. Simplicity is proposed as a desire to take the appropriate amount from the natural world and an acceptance of one’s circumstances. Those possessing simplicity will not fall victim to the …


Analysis Of Sat And Isat Scores For Madison School District In Rexburg, Idaho, Holly Dawn Palmer 2020 Utah State University

Analysis Of Sat And Isat Scores For Madison School District In Rexburg, Idaho, Holly Dawn Palmer

Undergraduate Honors Capstone Projects

Testing is an integral part of measuring education. If used properly SAT scores can be compared across the nation, and statewide tests can compare different school districts to each other if done properly to avoid certain pitfalls (Fetler, 1991). However, if tests do not have a significant impact on a student, their motivation to take the test will be low and test quality cannot be assumed. When the state funds two separate tests for their students but only one has a significant impact on the student, how should the scores for each test be used, and is it okay to …


The Two Types Of Society: Computationally Revealing Recurrent Social Formations And Their Evolutionary Trajectories, Lux Miranda 2020 Utah State University

The Two Types Of Society: Computationally Revealing Recurrent Social Formations And Their Evolutionary Trajectories, Lux Miranda

Undergraduate Honors Capstone Projects

Comparative social science has a long history of attempts to classify societies and cultures in terms of shared characteristics. However, only recently has it become feasible to conduct quantitative analysis of large historical datasets to mathematically approach the study of social complexity and classify shared societal characteristics. Such methods have the potential to identify recurrent social formations in human societies and contribute to social evolutionary theory. However, in order to achieve this potential, repeated studies are needed to assess the robustness of results to changing methods and data sets. Using an improved derivative of the Seshat: Global History Databank, we …


Demystification Of Graph And Information Entropy, Bryce Frederickson 2020 Utah State University

Demystification Of Graph And Information Entropy, Bryce Frederickson

Undergraduate Honors Capstone Projects

Shannon entropy is an information-theoretic measure of unpredictability in probabilistic models. Recently, it has been used to form a tool, called the von Neumann entropy, to study quantum mechanics and network flows by appealing to algebraic properties of graph matrices. But still, little is known about what the von Neumann entropy says about the combinatorial structure of the graphs themselves. This paper gives a new formulation of the von Neumann entropy that describes it as a rate at which random movement settles down in a graph. At the same time, this new perspective gives rise to a generalization of von …


Equivalency Testing For Two Formulations Of A Clinical Laboratory Control Material, Jessica M. Hart 2020 University of Nebraska Medical Center

Equivalency Testing For Two Formulations Of A Clinical Laboratory Control Material, Jessica M. Hart

Capstone Experience: Master of Public Health

Clinical laboratory control materials are an integral part of legally-mandated and highly regulated quality control protocols in all clinical laboratories. These controls ensure accurate performance of the laboratory testing and instrumentation used to produce medical test results for millions of patients. It is of clinical and public health interest to ensure the diagnostic test results which affect so many people are regulated by the most accurate and precise controls.

Formulation changes in control materials have the potential to impact laboratory quality control. In this study, data from two formulations of a hematology control were compared to assess equivalency of the …


Predicting The Federal Funds Rate, Danielle Herzberg 2020 University of Lynchburg

Predicting The Federal Funds Rate, Danielle Herzberg

Undergraduate Theses and Capstone Projects

This thesis examines various economic indicators to select those that are the most significant in a predictive model of the Effective Federal Funds Rate. Three different statistical models were built to show how monetary policy changed over time. These three models frame the last economic downturns in the United States; the tech bubble, the housing bubble, and the Great Recession. Many iterations of statistical regressions were conducted in order to achieve the final three models that highlight variables with the highest levels of significance. It is important to note the economic data has high levels of autocorrelation, and that these …


Applications Of Machine Learning In High-Frequency Trade Direction Classification, Jared E. Hansen 2020 Utah State University

Applications Of Machine Learning In High-Frequency Trade Direction Classification, Jared E. Hansen

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

The correct assignment of trades as buyer-initiated or seller-initiated is paramount in many quantitative finance studies. Simple decision rule methods have been used for signing trades since many data sets available to researchers do not include the sign of each trade executed. By utilizing these decision rule methods, as well as engineering new variables from available data, we have demonstrated that machine learning models outperform prior methods for accurately signing trades as buys and sells, achieving state-of-the-art results. The best model developed was 4.5 percentage points more accurate than older methods when predicting onto unseen data. Since finance and economics …


On Arnold–Villasenor Conjectures For Characterizaing Exponential Distribution Based On Sample Of Size Three, George Yanev 2020 The University of Texas Rio Grande Valley

On Arnold–Villasenor Conjectures For Characterizaing Exponential Distribution Based On Sample Of Size Three, George Yanev

School of Mathematical & Statistical Sciences Faculty Publications

Arnold and Villasenor [4] obtain a series of characterizations of the exponential distribution based on random samples of size two. These results were already applied in constructing goodness-of-fit tests. Extending the techniques from [4], we prove some of Arnold and Villasenor’s conjectures for samples of size three. An example with simulated data is discussed.


The Effects Of Zoledronate And Sleep Deprivation On The Distal Femur Trabecular Thickness Of Ovariectomized Rats: Application Of Different Statistical Methods, Erin Nolte 2020 Chapman University

The Effects Of Zoledronate And Sleep Deprivation On The Distal Femur Trabecular Thickness Of Ovariectomized Rats: Application Of Different Statistical Methods, Erin Nolte

Student Scholar Symposium Abstracts and Posters

Osteoporosis is a disease that causes the degradation of bone, leading to an increased risk of fracture. 1 in 3 women over the age of 50 will be affected by Osteoporosis. This study aims to understand how bone is affected by sleep deprivation in estrogen-deficient rats, and how Zoledronate might negate the inimical effects of sleep deprivation on bone. As bone mineral density (BMD) is a crude evaluation of the architectural changes seen in Osteoporosis, trabecular thickness may serve as a better single evaluation of bone health. 31 Wistar female rats were ovariectomized and separated into 4 random groups. The …


Motivational Predictors Of Academic Risk-Taking, Danette Dee Barber 2020 University of Nevada, Las Vegas

Motivational Predictors Of Academic Risk-Taking, Danette Dee Barber

UNLV Theses, Dissertations, Professional Papers, and Capstones

Students benefit when they are willing to engage in optimal challenges (Clifford, 1991). Engagement in challenges, however, comes with academic risks, as failure may be a result. This study investigated motivational factors, including expectancy, subjective task value, mastery goal orientation, and performance avoidance goal orientation as predictors of achievement-related outcomes, including course grade and academic risk-taking. Data were collected from 317 university students enrolled in education classes. Students were given a reading passage and asked to choose questions to answer based on the passage. Students who chose harder questions were categorized as taking more risk. Students also answered questions about …


'Lmshapemaker': Utilizing The 'Rmapshaper' R Package To Modify Shapefiles For Use In Linked Micromap Plots, Braden D. Probst 2020 Utah State University

'Lmshapemaker': Utilizing The 'Rmapshaper' R Package To Modify Shapefiles For Use In Linked Micromap Plots, Braden D. Probst

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

In order to effectively create map-based visualizations, some map modifications need to be conducted to ensure the map is readable and interpretable. There are several issues that need to be addressed to achieve this. The boundaries of a country may be overly complex which is particularly true with coastal areas of countries. Regions may be small and not seen in the final plot, as is the case with many capital cities in the world’s countries such as Washington D.C. and the Federal District of Mexico City. In other countries, regions may geographically lie far away from the rest of the …


An Analysis Of Dredge Efficiency For Surfclam And Ocean Quahog Commercial Dredges, Leanne Poussard 2020 The University of Southern Mississippi

An Analysis Of Dredge Efficiency For Surfclam And Ocean Quahog Commercial Dredges, Leanne Poussard

Master's Theses

Between 1997 and 2011, The National Marine Fisheries Service conducted 50 depletion experiments to estimate survey gear efficiency and stock density for Atlantic surfclam (Spisula solidissima) and ocean quahog (Arctica islandica) populations using commercial hydraulic dredges. The Patch Model was formulated to estimate gear efficiency and organism density from the data. The range of efficiencies estimated is substantial, leading to uncertainty in the application of these estimates in stock assessment. Analysis of depletion experiment simulations showed that uncertainty in the estimates of gear efficiency from depletion experiments was reduced by higher numbers of dredge tows per experiment, more tow overlap …


Introduction To Research Statistical Analysis: An Overview Of The Basics, Christian Vandever 2020 HCA Healthcare

Introduction To Research Statistical Analysis: An Overview Of The Basics, Christian Vandever

HCA Healthcare Journal of Medicine

This article covers many statistical ideas essential to research statistical analysis. Sample size is explained through the concepts of statistical significance level and power. Variable types and definitions are included to clarify necessities for how the analysis will be interpreted. Categorical and quantitative variable types are defined, as well as response and predictor variables. Statistical tests described include t-tests, ANOVA and chi-square tests. Multiple regression is also explored for both logistic and linear regression. Finally, the most common statistics produced by these methods are explored.


Rdc Data Alternatives: Conducting Research During Covid-19, Kristi Thompson, Elizabeth Hill 2020 Western University

Rdc Data Alternatives: Conducting Research During Covid-19, Kristi Thompson, Elizabeth Hill

Western Libraries Presentations

Recent physical distancing protocols pertaining to the COVID-19 Pandemic have meant that RDC researchers need to find alternatives ways of carrying out their research. The Real Time Remote Access (RTRA) program offers one alternative way to access confidential Statistics Canada data. Other options include using the Statistics Canada public use files and analyzing data from other sources.

The presenters, data librarians from Western Libraries will discuss the differences between the data that can be accessed through the RTRA the RDC. RTRA data is a very useful option for some types of questions but also has some important limitations. We will …


Accurate Confidence Intervals For Risk Difference In Meta-Analysis With Rare Events, Tao Jiang, Baixin Cao, Guogen Shan 2020 Zhejiang Gongshang University

Accurate Confidence Intervals For Risk Difference In Meta-Analysis With Rare Events, Tao Jiang, Baixin Cao, Guogen Shan

Environmental & Global Health Faculty Research

Background: Meta-analysis provides a useful statistical tool to effectively estimate treatment effect from multiple studies. When the outcome is binary and it is rare (e.g., safety data in clinical trials), the traditionally used methods may have unsatisfactory performance. Methods: We propose using importance sampling to compute confidence intervals for risk difference in meta-analysis with rare events. The proposed intervals are not exact, but they often have the coverage probabilities close to the nominal level. We compare the proposed accurate intervals with the existing intervals from the fixed- or random-effects models and the interval by Tian et al. (2009). Results: We …


Effect Of Zinc On Microcystis Aeruginosa And Its Toxin Production, Jose L. Perez 2020 Seton Hall University

Effect Of Zinc On Microcystis Aeruginosa And Its Toxin Production, Jose L. Perez

Seton Hall University Dissertations and Theses (ETDs)

Cyanobacteria harmful algal blooms (CHABs) are globally increasing biomasses of detrimental cyanobacteria due to anthropogenic water phosphorous and nitrogen loading and climate change. CHABs often produce secondary metabolites, cyanotoxins, that cause harmful effects to organisms, most water systems, and socioeconomic infrastructures. Additionally, the presence of heavy metal pollutant runoff in CHAB affected environments may result in CHAB population changes – aggravating toxigenicity. Zinc metal resistance and stress response were studied in microcystin (MC) cyanotoxin-producing Microcystis aeruginosa UTEX LB 2385 (M. aeruginosa UTEX LB 2385) and non-MC producing Microcystis aeruginosa UTEX LB 2386 (M. aeruginosa UTEX LB 2386) cyanobacteria. Molecular analysis …


Logistic Growth Modeling With Markov Chain Monte Carlo Estimation, Jaehwa Choi, Jinsong Chen, Jeffrey R. Harring 2020 The George Washington University

Logistic Growth Modeling With Markov Chain Monte Carlo Estimation, Jaehwa Choi, Jinsong Chen, Jeffrey R. Harring

Journal of Modern Applied Statistical Methods

A new growth modeling approach is proposed to can fit inherently nonlinear (i.e., logistic) function without constraint nor reparameterization. A simulation study is employed to investigate the feasibility and performance of a Markov chain Monte Carlo method within Bayesian estimation framework to estimate a fully random version of a logistic growth curve model under manipulated conditions such as the number and timing of measurement occasions and sample sizes.


A Simulation Study On Increasing Capture Periods In Bayesian Closed Population Capture-Recapture Models With Heterogeneity, Ross M. Gosky, Joel Sanqui 2020 Appalachian State University

A Simulation Study On Increasing Capture Periods In Bayesian Closed Population Capture-Recapture Models With Heterogeneity, Ross M. Gosky, Joel Sanqui

Journal of Modern Applied Statistical Methods

Capture-Recapture models are useful in estimating unknown population sizes. A common modeling challenge for closed population models involves modeling unequal animal catchability in each capture period, referred to as animal heterogeneity. Inference about population size N is dependent on the assumed distribution of animal capture probabilities in the population, and that different models can fit a data set equally well but provide contradictory inferences about N. Three common Bayesian Capture-Recapture heterogeneity models are studied with simulated data to study the prevalence of contradictory inferences is in different population sizes with relatively low capture probabilities, specifically at different numbers of …


Doubling Time Of The Covid-19 Epidemic By Province, China, Kamalich Muniz-Rodriguez, Gerardo Chowell, Chi-Hin Cheung, Dongyu Jia, Po-Ying Lai, Yiseul Lee, Manyun Liu, Sylvia Ofori, Kimberlyn M. Roosa, Lone Simonsen, Cecile Viboud, Isaac Fung 2020 Georgia Southern University, Jiann-Ping Hsu College of Public Health

Doubling Time Of The Covid-19 Epidemic By Province, China, Kamalich Muniz-Rodriguez, Gerardo Chowell, Chi-Hin Cheung, Dongyu Jia, Po-Ying Lai, Yiseul Lee, Manyun Liu, Sylvia Ofori, Kimberlyn M. Roosa, Lone Simonsen, Cecile Viboud, Isaac Fung

Biostatistics, Epidemiology & Environmental Health Sciences: Faculty Publications

In China, the doubling time of the coronavirus disease epidemic by province increased during January 20–February 9, 2020. Doubling time estimates ranged from 1.4 (95% CI 1.2–2.0) days for Hunan Province to 3.1 (95% CI 2.1–4.8) days for Xinjiang Province. The estimate for Hubei Province was 2.5 (95% CI 2.4–2.6) days.


Forecasting San Francisco Bay Area Rapid Transit (Bart) Ridership, Swee K. Chew, Alec Lepe, Aaron Tomkins, Peter Scheirer 2020 Southern Methodist University (SMU)

Forecasting San Francisco Bay Area Rapid Transit (Bart) Ridership, Swee K. Chew, Alec Lepe, Aaron Tomkins, Peter Scheirer

SMU Data Science Review

In this paper, we present a forecasting analysis of the San Francisco Bay Area Rapid Transit (BART) ridership data utilizing a number of different time series methods. BART is a major public transportation system in the Bay Area and it relies heavily on its riders' fares; having models that generate accurate ridership numbers better enables the agency to project revenue and help manage future expenses. For our time series modeling, we utilized autoregressive integrated moving average (ARIMA), deep neural networks (DNN), state space models, and long short-term memory (LSTM) to predict monthly ridership. As there is such a wide range …


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