Statistics and Probability Commons^™

Calculation And Statistical Analysis Of Wins Above Replacement, Joshua Taylor

Departmental Honors & Graduate Capstone Projects

The Wins Above Replacement (WAR) statistic in Major League Baseball is a prominent metric used to estimate player value by quantifying all aspects of play in terms of wins added to a baseball team. We will use R to calculate WAR for all players from 1871 to 2012 and use data from those years to construct multivariate predictive models to attempt to estimate WAR for players from 2013 to 2024. We find strong correlations between predicted and actual WAR values for most models, with the exception of the polynomial predictive model for non-qualified pitchers.

Bayesian Estimation Of A Pragmatic Model For Monetary Policy Analysis: The Case Of Pakistan, Shahzad Ahmad, Waliullah .

CBER Conference

In this study, Bayesian maximum likelihood estimation of quarterly projections model for Pakistan as presented, as documented in Ahmad & Pasha (2015). Estimation results based on quarterly data from 2001 to 2023 show substantial differences in values of estimated versus calibrated parameters related to aggregate demand, aggregate supply, monetary policy rule and exogenous shock processes. The aim of this study is to compare forecasting performance for key macro variables. It shows that the estimated model provides more precise forecasts in case of headline inflation, real GDP growth, interest rate and exchange rate over 8-quarters forecast horizon. An estimated model for …

Monetary Policy In Good Times And In Bad: Empirical Evidence From Pakistan, Haider Ali

CBER Conference

A significant body of literature explores and establishes the impact of monetary policy on output and prices, at least in the short run. However, the subsequent question is whether this effect is symmetric concerning the various states of the economy (see, Tenreyro and Thwaites, 2016; Bernstein, 2021; Eichenbaum et al., 2022; among others). This study contributes to the literature on state-dependent (non-linear) effects of unanticipated monetary policy shocks according to two important features of the economy. The amount of slack in the economy and the amount of the public-sector footprint in the market. Evaluating state-dependent effects is crucial because assuming …

Unlocking The Power Of Data: Enhancing Public Policy Through Advanced Data Infrastructure And Language Model Analysis, Zahid Asghar

CBER Conference

Data is the fundamental building block for advancements in artificial intelligence (AI), general AI (GAI), machine learning (ML), and large language models (LLMs). This study emphasizes the critical need for robust data infrastructure, arguing that without it, countries cannot fully benefit from technological advancements in various economic sectors. Governments possess vast repositories of both structured and unstructured data across multiple domains such as the judiciary, parliaments, and civil bureaucracy. However, these potential goldmines remain untapped due to inadequate data management capabilities and a lack of appreciation for the necessity of high-quality data. The research identifies key issues in public data …

The Energy Efficiency Price Premium Of Residential Buildings In Three Italian Regions, Elena Giarda, Demetrio Panarello

CBER Conference

The aim of this paper is to investigate whether a higher energy efficiency of residential buildings translates into higher house prices in Italy. We employ novel, and almost unexploited, data on Energy Performance Certificates of three Italian regions (EmiliaRomagna, Lombardy and Piedmont) and merge them with house prices and socioeconomic variables at various aggregation levels. The relationship between house prices and energy efficiency is estimated by means of hedonic regression models, quantile regressions and fixed effects panel data models. Our results reveal the existence of an energy-efficiency price premium in the three regions, with significant differences among them. Heterogeneity is …

Conditional Cooperation With Longer Memory, Nikoleta E. Glynatsi, Ethan Akin, Martin A. Nowak, Christian Hilbe

Mathematics and Statistics Faculty Research & Creative Works

Direct reciprocity is a wide-spread mechanism for the evolution of cooperation. In repeated interactions, players can condition their behavior on previous outcomes. A well-known approach is given by reactive strategies, which respond to the coplayer's previous move. Here, we extend reactive strategies to longer memories. A reactive-n strategy takes into account the sequence of the last n moves of the coplayer. A reactive-n counting strategy responds to how often the coplayer cooperated during the last n rounds. We derive an algorithm to identify the partner strategies within these strategy sets. Partner strategies are those that ensure mutual cooperation without exploitation. …

Customer Data And The Digital Age, Mahdi Ansari

CBER Conference

Data is widely regarded as the most valuable resource in today’s economy, yet its value often eludes precise quantification. This paper examines customer data as an intangible capital asset and addresses the challenge of measuring its impact. A novel database was created by merging Compustat with online clickstream data capturing the activity of approximately 200 million users, providing proxies for data inflow based on visit metrics. The analysis documents that the distribution of firms’ customer data stocks follows a rightskewed log-normal pattern with a fat tail. Additionally, a positive relationship emerges between sales and data inflow, data stock, profit, and …

If You Can’T Beat Them Join Them: Empirical Assessment Into How Integrating Conventional Taxis On The Uber App Impacts Conventional Taxi Ridership, Shahmeer Mohsin

CBER Conference

Since the emergence of ride-hailing platforms like Uber, conventional taxi ridership has taken a severe hit. Taxi-hailing apps like Curb and Arro have allowed conventional taxis to jump on the platform economy bandwagon and offer a similar service to ride-hailing platforms. Despite the emergence of these taxi-hailing apps, strong lock-in effects and high switching costs of popular ride-hailing platforms (Uber, Lyft, etc.) restrict the ridership volumes of conventional taxis. Recently, the ride-hailing platform, Uber has started to add conventional taxis on its app under increasing pressure from Cities and conventional taxi associations. Such integrations have the potential of increasing conventional …

Statistical Analysis For Pre- And Post- Assessments Of Sdq And Idela Scores, Diego Murillo, Franceli L. Cibrian

Student Scholar Symposium Abstracts and Posters

This research aimed to assess the potential of Mazi Umntanakho ("Know Your Child") in tracking developmental milestones in young children. Mazi is a WhatsApp-based conversational agent that assists South African home visitors in evaluating and monitoring children's socio-emotional skills using the Strengths and Difficulties Questionnaire (SDQ) and the International Development and Early Learning Assessment (IDELA). A field study was conducted in low-income South African communities, where 95 home visitors assessed 1,208 children. This detailed analysis of the data was collected during that deployment, focusing on investigating whether assessment scores improved over time and whether the length of time between assessments …

Does A Name Make A Difference? Teaching Random Selection In The Classroom, Venessa Singhroy, Rommel Robertson, Kostas Stroumbakis

Numeracy

In Statistics education, it is crucial to emphasize the foundational significance of random selection, which underpins statistical methodologies and ensures unbiased representation of populations in samples. However, students often struggle to grasp the concept’s complexities, leading to challenges in applying random selection methods effectively. This paper examines the gap between students’ theoretical understanding of randomness and their practical application of this concept. Using an Explanatory Sequential Design, this study presents an instructional activity aimed at teaching the concept of randomness in the selection process and proposes modifications to enhance student comprehension. The activity, implemented in undergraduate Statistics and Psychology courses, …

A Latent Class Assessment Of Healthcare Access Factors And Disparities In Breast Cancer Care Timeliness, Matthew Dunn, Didong Li, Marc Emerson, Caroline Thompson, Hazel Nichols, Sarah Van Alsten, Mya Roberson, Stephanie Wheeler, Lisa Carey, Terry Hyslop, Jennifer Elston Lafata, Melissa Troester

Kimmel Cancer Center Faculty Papers

BACKGROUND: Delays in breast cancer diagnosis and treatment lead to worse survival and quality of life. Racial disparities in care timeliness have been reported, but few studies have examined access at multiple points along the care continuum (diagnosis, treatment initiation, treatment duration, and genomic testing).

METHODS AND FINDINGS: The Carolina Breast Cancer Study (CBCS) Phase 3 is a population-based, case-only cohort (n = 2,998, 50% black) of patients with invasive breast cancer diagnoses (2008 to 2013). We used latent class analysis (LCA) to group participants based on patterns of factors within 3 separate domains: socioeconomic status ("SES"), "care barriers," and …

Multiple And Nonexistence Of Positive Solutions For A Class Of Fractional Differential Equations With P-Laplacian Operator, Haoran Zhang, Zhaocai Hao, Martin Bohner

Mathematics and Statistics Faculty Research & Creative Works

Research about multiple positive solutions for fractional differential equations is very important. Based on some outstanding results reported in this field, this paper continues the focus on this topic. By using the properties of the Green function and generalized Avery–Henderson fixed point theorem, we derive three positive solutions of a class of fractional differential equations with a p-Laplacian operator. We also study the nonexistence of positive solutions to the eigenvalue problem of the equation. Three examples are given to illustrate our main result.

(R2101) Analysis Of Map/Ph/1 Queueing Inventory System With Two Commodity, Working Vacation, (S, S) Replenishment Policy, Essential And Optional Repair, G. Ayyappan, N. Arulmozhi

Applications and Applied Mathematics: An International Journal (AAM)

We examine a queueing inventory model with single server which can offer two types of inventory items: main item (commodity I) and complementary item (commodity II). We assume both commodities have a finite capacity Si, i = 1, 2. Customers reach the system by following the Markovian arrival process (MAP). The service times are considered to be phase-type (PH) distribution. We have considered no customer in the system, even inventory level is positive; the server will start the working vacation, and any customer that arrives during working vacation, the server provides slow service. If an item is not available, the …

(R2095) On Discrete Hypoexponential Distribution And Integer-Valued Autoregressive Process, K. Krishnakumari, Dais George

Applications and Applied Mathematics: An International Journal (AAM)

Discrete distributions provide a substantive contribution in modeling real world frame work. Though a lot of discrete distributions are available in literature, they are inappropriate to model many practical situations. The conventional discrete distributions like geometric, Negative Binomial and Poisson have limited applications in modeling count and lifetime data. This paper introduces a new two parameter discrete distribution namely, discrete hypoexponential distribution by discretizing the well known hypoexponential distribution. Various distributional and structural properties of the proposed distribution are studied. We introduce a first order auto regressive process with the newly proposed distribution as marginal and study the properties. Depending …

Optimization Of Markov Chain Modeling In Predicting College Student Retention, Kien Nguyen

Journal of Global Education and Research

College student retention is one of the most important metrics in higher education. With institutions across the US facing decreasing enrollment, developing a reliable retention prediction method is crucial. In recent years, the use of the Markov chain model in forecasting student enrollment and progression has become more common, but there is little work on its application in student retention. One key factor in determining this model's effectiveness is what parameters should be used in the student population’s segmentation or grouping. This study presents a rigorous algorithm, coupled with a prediction model, capable of selecting parameters that provide the most …

Statistics With Actuarial Emphasis, Zachariah Yonker

Honors Projects

This report presents the findings of a survey conducted among members of the Grand Valley State University Dungeons & Dragons Club, focusing on member age, gender, habits, and game preferences. The survey, administered during the Fall 2024 semester, received 31 responses, with 30 being completed and 1 partially finished, representing approximately 25% of active club members. Key findings via the Statistical Analysis System (SAS) include a diverse range of preferences and opinions about Dungeons & Dragons classes, as well as a consensus on the most difficult challenge of the activity in addition to favorite aspects of Dungeons & Dragons.

Variable Selection In Distance Metric Learning And Triplet Constraints For Deep Learning Based Ordinal Classification, James D. Clothier

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

The purpose of this research is to augment linear and kernelized ordinal distance metric learning (L/KODML) techniques with a proposed variable selection methodology that integrates the Sequential Multi-Response Feature Selection (SMuRFS) algorithm. Additionally, we aim to embed ordinal triplet constraints into a deep learning architecture, and to propose a general framework for deep learning-based ordinal classification. A variety of simulation studies and real data experiments were conducted to evaluate the various methodologies. For the distance metric learning and variable selection, results showed that the integration of SMuRFS performed effective variable selection and improved prediction accuracy. For the triplet constraints, incorporating …

Performance Of Acoustic Telemetry And Space Use Of Pallid Sturgeon In The Lower Platte River, Nebraska, Christopher F. Pullano

School of Natural Resources: Dissertations, Theses, and Student Research

Pallid Sturgeon (Scaphirhynchus albus) are centenarian, potamodromous, rheophiles that historically occupied the Missouri River and Mississippi River basins. Listed on the U.S. Endangered Species Act in 1990, population declines are attributed to habitat fragmentation and degradation, as well as overharvest, and hybridization. A knowledge gap exists regarding the extent to which tributaries facilitate key life stages for Pallid Sturgeon. This study evaluated the capacity of acoustic telemetry to monitor the movements of Pallid Sturgeon in a shallow, braided tributary to the Missouri River. The specific objectives were to (1) evaluate the environmental variables influencing the performance of acoustic …

(R2098) Dynamic Analysis Of Stochastic Leslie-Gower Biological Predator-Prey Model With Prey Cannibalism, Sada Nand Prasad, Itendra Kumar Universiry Of Delhi, India, Pawan Kumar

Applications and Applied Mathematics: An International Journal (AAM)

In this paper, we study the dynamical analysis of a stochastic Leslie–Gower biological predator– prey model. Earlier, the Leslie–Gower model was studied in the context of biological systems, including cases involving cannibalism. In our model, we investigate the dynamic properties of a stochastic Leslie–Gower predator–prey ecological system using the stability of invariant measures on invariant sets, where the invariant measures are shown to be ergodic. We also conduct a threshold analysis to study the stochastic persistence and extinction of species. Stochastic bifurcation is also examined. The theoretical results are supported by numerical simulations and examples. Intra-species competition is considered and …

(R2116) The Novel Garima Distribution Properties And Nuclear Data Application, Murat Aygün, Ayşe Metin Karakaş

Applications and Applied Mathematics: An International Journal (AAM)

This research introduces a new two-parameter Marshall-Olkin Garima distribution model. The novel model has many sub-models that are useful in modeling real-life data, such as the extended Garima distribution, exponentiated Garima distribution, exponential distribution, Lindley distribution, Kumaraswamy Garima distribution, and normal distribution. The proposed model demonstrates a high level of suitability in modeling both reliability and survival data. It is flexible in accommodating various failures. The quantile function, density shapes, hazard rate functions, and order statistics are a few of the statistical features that have been explored. Maximum likelihood estimation methods were employed to estimate the parameters. Using five data …