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Full-Text Articles in Physical Sciences and Mathematics

"Who Wrote The Epistle, God Only Knows": A Statistical Authorial Analysis Of Hebrews In Comparison With Pauline And Lukan Literature, Benjamin J. Erickson Apr 2024

"Who Wrote The Epistle, God Only Knows": A Statistical Authorial Analysis Of Hebrews In Comparison With Pauline And Lukan Literature, Benjamin J. Erickson

Senior Honors Theses

The authorship of Hebrews has been a point of contention for scholars for the past two millennia. While the epistle is traditionally attributed to Paul, many scholars assert that it carries thematic, structural, and stylistic differences from the remainder of his extant epistles; therefore, many other possible authors have been proposed. Of these, only Luke has other New Testament writings. Therefore, this project conducts a statistical comparison of Hebrews to the Pauline and Lukan corpora using stylometric authorial analysis methods. This analysis demonstrates that Hebrews is stylistically closer to Lukan literature than Pauline (but not to a significant degree), and …


A Monte Carlo Analysis Of Seven Dichotomous Variable Confidence Interval Equations, Morgan Juanita Dubose Apr 2022

A Monte Carlo Analysis Of Seven Dichotomous Variable Confidence Interval Equations, Morgan Juanita Dubose

Masters Theses & Specialist Projects

Department of Psychological Sciences Western Kentucky University There are two options to estimate a range of likely values for the population mean of a continuous variable: one for when the population standard deviation is known and another for when the population standard deviation is unknown. There are seven proposed equations to calculate the confidence interval for the population mean of a dichotomous variable: normal approximation interval, Wilson interval, Jeffreys interval, Clopper-Pearson, Agresti-Coull, arcsine transformation, and logit transformation. In this study, I compared the percent effectiveness of each equation using a Monte Carlo analysis and the interval range over a range …


Trade Bait: Season 3, Ben Bagley Oct 2021

Trade Bait: Season 3, Ben Bagley

WWU Honors College Senior Projects

A 5-episode podcast series dissecting the use of statistics in the NFL and NFL Media


Guidelines For Regression Analysis In Sas And R: A Case Study, Sarah Milligan May 2021

Guidelines For Regression Analysis In Sas And R: A Case Study, Sarah Milligan

Honors Program Theses and Projects

When a player is a free agent, an individual who is able to sign to any team, one wonders what their best option is. Will signing with Team A or Team B provide them with the largest salary? What factors will affect their salary the most? Does last year’s statistics have a strong impact on next year’s salary? These questions can be answered by performing a regression analysis on previous years data. The primary focus of this project is to determine the most important variables related to an NBA salary. Likewise, the statistical programs SAS and R will be compared …


Using Stability To Select A Shrinkage Method, Dean Dustin May 2020

Using Stability To Select A Shrinkage Method, Dean Dustin

Department of Statistics: Dissertations, Theses, and Student Work

Shrinkage methods are estimation techniques based on optimizing expressions to find which variables to include in an analysis, typically a linear regression. The general form of these expressions is the sum of an empirical risk plus a complexity penalty based on the number of parameters. Many shrinkage methods are known to satisfy an ‘oracle’ property meaning that asymptotically they select the correct variables and estimate their coefficients efficiently. In Section 1.2, we show oracle properties in two general settings. The first uses a log likelihood in place of the empirical risk and allows a general class of penalties. The second …


The Role Of Topography, Soil, And Remotely Sensed Vegetation Condition Towards Predicting Crop Yield, Trenton E. Franz, Sayli Pokal, Justin P. Gibson, Yuzhen Zhou, Hamed Gholizadeh, Fatima Amor Tenorio, Daran Rudnick, Derek M. Heeren, Matthew F. Mccabe, Matteo Ziliani, Zhenong Jin, Kaiyu Guan, Ming Pan, John Gates, Brian Wardlow Jan 2020

The Role Of Topography, Soil, And Remotely Sensed Vegetation Condition Towards Predicting Crop Yield, Trenton E. Franz, Sayli Pokal, Justin P. Gibson, Yuzhen Zhou, Hamed Gholizadeh, Fatima Amor Tenorio, Daran Rudnick, Derek M. Heeren, Matthew F. Mccabe, Matteo Ziliani, Zhenong Jin, Kaiyu Guan, Ming Pan, John Gates, Brian Wardlow

School of Natural Resources: Faculty Publications

Foreknowledge of the spatiotemporal drivers of crop yield would provide a valuable source of information to optimize on-farm inputs and maximize profitability. In recent years, an abundance of spatial data providing information on soils, topography, and vegetation condition have become available from both proximal and remote sensing platforms. Given the wide range of data costs (between USD $0−50/ha), it is important to understand where often limited financial resources should be directed to optimize field production. Two key questions arise. First, will these data actually aid in better fine-resolution yield prediction to help optimize crop management and farm economics? Second, what …


Sensitivity Analyses For Tumor Growth Models, Ruchini Dilinika Mendis Apr 2019

Sensitivity Analyses For Tumor Growth Models, Ruchini Dilinika Mendis

Masters Theses & Specialist Projects

This study consists of the sensitivity analysis for two previously developed tumor growth models: Gompertz model and quotient model. The two models are considered in both continuous and discrete time. In continuous time, model parameters are estimated using least-square method, while in discrete time, the partial-sum method is used. Moreover, frequentist and Bayesian methods are used to construct confidence intervals and credible intervals for the model parameters. We apply the Markov Chain Monte Carlo (MCMC) techniques with the Random Walk Metropolis algorithm with Non-informative Prior and the Delayed Rejection Adoptive Metropolis (DRAM) algorithm to construct parameters' posterior distributions and then …


The Psychology Of Baseball: How The Mental Game Impacts The Physical Game, Kiera Dalmass Apr 2018

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 …


Sabermetrics - Statistical Modeling Of Run Creation And Prevention In Baseball, Parker Chernoff Mar 2018

Sabermetrics - Statistical Modeling Of Run Creation And Prevention In Baseball, Parker Chernoff

FIU Electronic Theses and Dissertations

The focus of this thesis was to investigate which baseball metrics are most conducive to run creation and prevention. Stepwise regression and Liu estimation were used to formulate two models for the dependent variables and also used for cross validation. Finally, the predicted values were fed into the Pythagorean Expectation formula to predict a team’s most important goal: winning.

Each model fit strongly and collinearity amongst offensive predictors was considered using variance inflation factors. Hits, walks, and home runs allowed, infield putouts, errors, defense-independent earned run average ratio, defensive efficiency ratio, saves, runners left on base, shutouts, and walks per …


On The Performance Of Some Poisson Ridge Regression Estimators, Cynthia Zaldivar Mar 2018

On The Performance Of Some Poisson Ridge Regression Estimators, Cynthia Zaldivar

FIU Electronic Theses and Dissertations

Multiple regression models play an important role in analyzing and making predictions about data. Prediction accuracy becomes lower when two or more explanatory variables in the model are highly correlated. One solution is to use ridge regression. The purpose of this thesis is to study the performance of available ridge regression estimators for Poisson regression models in the presence of moderately to highly correlated variables. As performance criteria, we use mean square error (MSE), mean absolute percentage error (MAPE), and percentage of times the maximum likelihood (ML) estimator produces a higher MSE than the ridge regression estimator. A Monte Carlo …


Investigating The Student Enrollment Decision At Wku, Alec Brown Sep 2017

Investigating The Student Enrollment Decision At Wku, Alec Brown

Mahurin Honors College Capstone Experience/Thesis Projects

The purpose of this research is to investigate the relationships between the enrollment decision of first-time, first-year students admitted to Western Kentucky University and the amount of financial aid awarded, as well as demographic information. The Division of Enrollment Management provided a SAS dataset containing various information about all WKU students admitted in 2013, 2014, and 2015. Additionally, information about the 2016 class of admitted students was provided. The data has been analyzed in SAS Enterprise Miner. We performed analysis using decision tree modeling and logistic regression modeling. Results of these two procedures indicated the importance of credit hours earned …


Gilmore Girls And Instagram: A Statistical Look At The Popularity Of The Television Show Through The Lens Of An Instagram Page, Brittany Simmons May 2017

Gilmore Girls And Instagram: A Statistical Look At The Popularity Of The Television Show Through The Lens Of An Instagram Page, Brittany Simmons

Student Scholar Symposium Abstracts and Posters

After going on the Warner Brothers Tour in December of 2015, I created a Gilmore Girls Instagram account. This account, which started off as a way for me to create edits of the show and post my photos from the tour turned into something bigger than I ever could have imagined. In just over a year I have over 55,000 followers. I post content including revival news, merchandise, and edits of the show that have been featured in Entertainment Weekly, Bustle, E! News, People Magazine, Yahoo News, & GilmoreNews.

I created a dataset of qualitative and quantitative outcomes from my …


Preparedness Of Hospitals In The Republic Of Ireland For An Influenza Pandemic, An Infection Control Perspective, Mary Reidy, Fiona Ryan, Dervla Hogan, Seán Lacey, Claire Buckley Sep 2015

Preparedness Of Hospitals In The Republic Of Ireland For An Influenza Pandemic, An Infection Control Perspective, Mary Reidy, Fiona Ryan, Dervla Hogan, Seán Lacey, Claire Buckley

Department of Mathematics Publications

When an influenza pandemic occurs most of the population is susceptible and attack rates can range as high as 40–50 %. The most important failure in pandemic planning is the lack of standards or guidelines regarding what it means to be ‘prepared’. The aim of this study was to assess the preparedness of acute hospitals in the Republic of Ireland for an influenza pandemic from an infection control perspective.


Ua56/1 Fact Book, Wku Institutional Research Jan 2015

Ua56/1 Fact Book, Wku Institutional Research

WKU Archives Records

Statistical and demographic profile of WKU.


From Unbiased Numerical Estimates To Unbiased Interval Estimates, Baokun Li, Gang Xiang, Vladik Kreinovich, Panagios Moscopoulos Aug 2012

From Unbiased Numerical Estimates To Unbiased Interval Estimates, Baokun Li, Gang Xiang, Vladik Kreinovich, Panagios Moscopoulos

Departmental Technical Reports (CS)

One of the main objectives of statistics is to estimate the parameters of a probability distribution based on a sample taken from this distribution. Of course, since the sample is finite, the estimate X is, in general, different from the actual value x of the corresponding parameter. What we can require is that the corresponding estimate is unbiased, i.e., that the mean value of the difference X - x is equal to 0: E[X] = x. In some problems, unbiased estimates are not possible. We show that in some such problems, it is possible to have interval unbiased estimates, i.e., …


Helin Institutions' Collection Statistics From Fy 10 To Fy 11, Martha Rice Sanders Jul 2011

Helin Institutions' Collection Statistics From Fy 10 To Fy 11, Martha Rice Sanders

HELIN Collection Statistics

Statistical information about the total number of item and holdings (serials) records held by each HELIN member institution as of June 30, 2010, and June 30, 2011. Gives the percentage of growth for each institution. Additionally, a chart and statistics for the number of item records held by each HELIN member institution as of June 30, 2011. A Chart of e-book collection totals and the libraries to which they belong. Finally, a chart of serials holdings for both paper (plus microform, etc.) and electronic journals, including the CRIARL libraries.


How Do You Interpret A Confidence Interval?, Paul Savory Jan 2008

How Do You Interpret A Confidence Interval?, Paul Savory

Industrial and Management Systems Engineering: Instructional Materials

A confidence interval (CI) is an interval estimate of a population parameter. Instead of estimating the parameter by a single value, a point estimate, an interval likely to cover the parameter is developed. Many student incorrectly interpret the meaning of a confidence interval. This paper offers a quick overview of how to correctly interpret a confidence interval.


Why Divide By (N-1) For Sample Standard Deviation?, Paul Savory Jan 2008

Why Divide By (N-1) For Sample Standard Deviation?, Paul Savory

Industrial and Management Systems Engineering: Instructional Materials

In statistics, the sample standard deviation is a widely used measure of the variability or dispersion of a data set. The standard deviation of a data set is the square root of its variance. In calculating the sample standard deviation, the divisor is the number of samples in the data set minus one (n-1) rather than n. This often confuses students. This paper offers a quick overview of why the divisor is (n-1) for calculating the sample standard deviation.


Heckman's Methodology For Correcting Selectivity Bias : An Application To Road Crash Costs, Margaret Giles Jan 2001

Heckman's Methodology For Correcting Selectivity Bias : An Application To Road Crash Costs, Margaret Giles

Research outputs pre 2011

Aggregate road crash costs are traditionally determined using average costs applied to incidence figures found in Police-notified crash data. Such data only comprise a non-random sample of the true population of road crashes, the bias being due to the existence of crashes that are not notified to the Police. The traditional approach is to label the Police-notified sample as 'non-random' thereby casting a cloud over data analyses using this sample. Heckman however viewed similar problems as 'omitted variables' problems in that the exclusion of some observations in a systematic manner (so-called selectivity bias) has inadvertently introduced the need for an …