Applied Statistics Commons^™

Optimizing Nba Roster Construction, Nick R. Riccardi

Sport Management - All Scholarship

This study aims to quantify the effect that complementary player types have on team success in the National Basketball Association. Using cluster analysis, player-seasons are redefined from their traditional basketball positions to better encompass the roles that players play. For the 10 seasons of data, the best player for each of the 30 teams in the league is determined and teams are grouped based on the cluster of their best player. Ordinary Least Squares regressions are performed to test what player types fit together best. The results of this study show the importance of complementary workers to a firm’s success.

A 3-Step, Open-Data, Ride-Hailing Ridership Model With Pricing Applications, Richard A. Mucci

Theses and Dissertations--Civil Engineering

Researchers and practitioners studied the effects ride-hailing had in cities before the covid-19 pandemic. Previous research found ride-hailing to produce negative externalities, such as reducing transit ridership and increasing congestion in various cities. Since the pandemic, ride-hailing ridership has nearly recovered to pre-pandemic levels in Chicago. Ride-hailing ridership has grown steadily since the pandemic while a rider’s willingness to share their trip stagnated. Ride-hailing ridership nearly recovering to pre-covid levels in Chicago suggests that transportation planners, and policy makers, will need to continue assessing the impacts ride-hailing trips have in their cities.

Pickup and drop off locations in the Chicago …

Investigating Flash Flood Occurrence Using Negative Binomial Models In Maryland, United States Of America, Zainab O. Akinsemoyin

College of Graduate Studies: Theses & Dissertations

Globally, as extreme weather patterns intensify, flash floods have emerged as one of the most destructive and immediate environmental threats. In Maryland, flash floods are particularly concerning due to its diverse topography and increasing urban development, which exacerbates runoff and overwhelms drainage systems. The state has experienced significant flash flood events, highlighting the need for effective models to manage risks and inform mitigation strategies. While regression models such as the Negative Binomial (NB) and Zero-Inflated Negative Binomial (ZINB) are commonly used for count data analysis, their application to flash flood modeling in the USA, including regions like Maryland, remains limited …

Measuring The Performance Of Sdgs In Provincial Level Using Regional Sustainable Development Index, Nurafiza Thamrin, Ika Yuni Wulansari, Puguh Bodro Irawan

Journal of Environmental Science and Sustainable Development

Measuring the national and sub-national progress in achieving such globally adopted development agendas as Sustainable Development Goals (SDGs) is particularly challenging due to data availability and compatibility of indicators to measure SDGs, especially in Indonesia. This paper attempts to measure the performance of sustainable development at the regional level in Indonesia by newly constructing a multidimensional composite index called the Regional Sustainable Development Index (RSDI). RSDI comprises four dimensions, covering comprehensive economic, social, environmental, and governance indicators. By applying factor analysis, the paper assesses the uncertainty of RSDI and the sensitivity of its composing indicators, then further investigates the relationship …

Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia

Journal of Nonprofit Innovation

Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.

Imagine Doris, who is …

Ohio Recovery Housing: Resident Risk And Outcomes Assessment, Elyjiah Potter, Bivin Sadler

SMU Data Science Review

Addiction and substance abuse disorder is a significant problem in the United States. Over the past two decades, the United States has faced a boom in substance abuse, which has resulted in an increase in death and disruption of families across the nation. The State of Ohio has been particularly hard hit by the crisis, with overdose rates nearly doubling the national average. Established in the mid 1970’s Sober Living Housing is an alcohol and substance use recovery model emphasizing personal responsibility, sober living, and community support. This model has been adopted by the Ohio Recovery Housing organization, which seeks …

Occupational And Environmental Factors Influencing Morale Of United States Federal Wildland Firefighters, Rachel M. Granberg, Ting Shen, Seth W. Pearson, Robin M. Verble

Psychological Science Faculty Research & Creative Works

Background. Wildland firefighters have physically and psychologically demanding jobs that can result in social, economic and health-related stress. Previous studies have examined the physiological and physical effects of a career in wildland fire, but fewer studies have addressed psychological effects, and to date, none have directly analyzed the hiring and work experiences of wildland firefighters. Aims. We surveyed work experiences, health and well-being, and morale of wildland firefighters, explored factors that can improve recruitment and retention, and summarized broad patterns. Methods. We conducted a voluntary anonymous survey of 708 federal wildland firefighters via an online platform over 2 months in …

Is The Declining Birthrate Really An Issue For The Economy?, Harsh Ramesh Pednekar, Theodore Lee, Darrion Chin

Introduction to Research Methods RSCH 202

This study aims to explore the complex implications of declining birth rates on the economy, focusing on GDP per capita as a crucial metric, and aims to uncover both potential opportunities and challenges stemming from this demographic transformation using regression analysis. Using a quantitative methodology and secondary data from OECD.stat, World Population Review, and World Bank, the study explores the relationship between declining birth rates and economic impacts. GDP per capita serves as an essential dependent variable, and it accounts for control variables such as labour force participation, literacy, and education levels, child dependence ratio, and physical capital. Past studies …

Bitcoin And South African Stock Market Returns During Covid-19 Pandemic: A Test Of The Safe-Haven Hypothesis, Akaninyene U. Udom, Sopuru W. Nnamani

CBN Journal of Applied Statistics (JAS)

This paper tests the safe-haven property of Bitcoin for South African stocks using Full and Diagonal BEKK-GARCH models. The study uses the Johannesburg stock exchange Top40 index, and bitcoin returns data before COVID-19 (August 2018 to December 2019) and during COVID-19 (January 2020 to June 2021). The results show that bitcoin cannot be considered as safe-haven for stocks in South Africa since it is weakly correlated with stock and had a high volatility during the Pandemic. Therefore, the safe-haven hypothesis of bitcoin on South African stocks is not true for the period under study. The policy implication is that bitcoin …

Generalized Ratio-Product Cum Regression Variance Estimator In Two-Phase Sampling, Isah Muhammad

CBN Journal of Applied Statistics (JAS)

This study develops a flexible and efficient generalized ratio-product cum regression type estimator of population variance utilizing auxiliary variable in two-phase sampling that incorporates the properties of ratio-type and product-type estimators. The properties of the estimator were derived using first order approximation. The theoretical conditions under which the precision and the flexibility of the estimator is better than some classical estimators are also provided. Empirical evidence from five real datasets suggests that the proposed estimator outperforms the classical variance, ratio variance, product, and exponential ratio type estimators in terms of precision and efficiency. The estimator can be utilized to provide …

Modelling The Naira Exchange Rate Dependence Using Static And Time-Varying Copula, Kabir Katata

CBN Journal of Applied Statistics (JAS)

This paper examines the dependence structure of different currencies versus the Nigerian Naira using constant and time-varying copula. Daily Naira/USD, Naira/Yuan, Naira/Pound, and Naira/Euro exchange rates from 23 December 2011 to 12 May 2020 were utilised. We fitted eight constant and time-varying copula families using the exchange rate standardised residuals. The study finds that the Naira exchange rate may be estimated with student t-copula, Symmetrized Joe-Clayton (SJC), or Rotated Gumbel copula models and Autoregressive (AR)– Glosten Jagannathan RunkleGeneralized Autoregressive Conditional Heteroscedastic (GJR-GARCH) (1,1) models with skewed t residuals for margins. The Naira exchange rate returns is timevarying, tail-dependent, and asymmetric. …

External Debt Pass-Through To Inflation In Nigeria, Emmanuel A. Asue, James V. Ikyaator

CBN Journal of Applied Statistics (JAS)

This study examines external debt pass-through to inflation in Nigeria using annual data from 1981 to 2020 based on structural vector autoregressive (SVAR) model. The results reveal that an increase in external debt service leads to a significant depreciation of the exchange rate, which leads to a contemporaneous increase in inflation, while the direct response of inflation to external debt is statistically not significant. The impulse response confirms these results. The forecast error variance decomposition depicts that future values of official exchange rate depend on external debt, inflation and external debt service. The study recommends that the Nigerian government should …

Financial Inclusion And Poverty Reduction In Nigeria: The Role Of Microfinance Institutions, Okwudili W. Ugwuoke, Oliver E. Ogbonna, Aye-Agele Freeman

CBN Journal of Applied Statistics (JAS)

This study investigates the role of microfinance institutions as a vehicle for driving financial inclusion and alleviating poverty in Nigeria using the EFinA 2018 household survey data. The probit model, propensity score matching, and average treatment effect methods are applied for the analyses. The study finds that financial inclusion driven by access to, and usage of products/services provided by microfinance institutions reduces poverty. The study recommends among others the need for increased access to microfinance products/services and an integrated poverty reduction policies that identifies microfinance institutions as a critical enabler

Mathematical Modeling Of The Impact Of Lobbying On Climate Policy, Andrew Jacoby, Claire Hannah, James Hutchinson, Jasmine Narehood, Aditi Ghosh, Padmanabhan Seshaiyer

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

The Use Of Regularization To Detect Racial Inequities In Pay Equity Studies: An Empirical Study And Reflections On Regulation Methods, Christopher M. Peña

Electronic Theses and Dissertations

Since the late 1970s, multiple linear regression has been the preferred method for identifying discrimination in pay. An empirical study on this topic was conducted using quantitative critical methods. A literature review first examined conflicting views on using multiple linear regression in pay equity studies. The review found that multiple linear regression is used so prevalently in pay equity studies because the courts and practitioners have widely accepted it and because of its simplicity and ability to parse multiple sources of variance simultaneously. Commentaries in the literature cautioned about errors in model specification, the use of tainted variables, and the …

Reducing Uncertainty In Sea-Level Rise Prediction: A Spatial-Variability-Aware Approach, Subhankar Ghosh, Shuai An, Arun Sharma, Jayant Gupta, Shashi Shekhar, Aneesh Subramanian

I-GUIDE Forum

Given multi-model ensemble climate projections, the goal is to accurately and reliably predict future sea-level rise while lowering the uncertainty. This problem is important because sea-level rise affects millions of people in coastal communities and beyond due to climate change's impacts on polar ice sheets and the ocean. This problem is challenging due to spatial variability and unknowns such as possible tipping points (e.g., collapse of Greenland or West Antarctic ice-shelf), climate feedback loops (e.g., clouds, permafrost thawing), future policy decisions, and human actions. Most existing climate modeling approaches use the same set of weights globally, during either regression or …

A Classical Fall Statistics Problem, Timothy Meyer

Cornhusker Economics

An evaluation of traditional baseball measures and suggestions for alternatives, centering on statistics related to the offensive quality of a player.

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 …

The Appropriateness Of Outlier Exclusion Approaches Depends On The Expected Contamination: Commentary On André (2022), Daniel Villanova

Marketing Faculty Publications and Presentations

In a recent article, André (2022) addressed the decision to exclude outliers using a threshold across conditions or within conditions and offered a clear recommendation to avoid within-conditions exclusions because of the possibility for large false-positive inflation. In this commentary, I note that André’s simulations did not include the situation for which within-conditions exclusion has previously been recommended—when across-conditions exclusion would exacerbate selection bias. Examining test performance in this situation confirms the recommendation for within-conditions exclusion in such a circumstance. Critically, the suitability of exclusion criteria must be considered in relationship to assumptions about data-generating mechanisms.

Statistical And Biological Analyses Of Acoustic Signals In Estrildid Finches, Moises Rivera

Dissertations, Theses, and Capstone Projects

Acoustic communication is a process that involves auditory perception and signal processing. Discrimination and recognition further require cognitive processes and supporting mechanisms in order to successfully identify and appropriately respond to signal senders. Although acoustic communication is common across birds, classical research has largely disregarded the perceptual abilities of perinatal altricial taxa. Chapter 1 reviews the literature of perinatal acoustic stimulation in birds, highlighting the disproportionate focus on precocial birds (e.g., chickens, ducks, quails). The long-held belief that altricial birds were incapable of acoustic perception in ovo was only recently overturned, as researchers began to find behavioral and physiological evidence …

Digital Economy, Institutional Quality And Economic Growth In Selected Countries, Olabode P. Olofin Mr.

CBN Journal of Applied Statistics (JAS)

This study examines the role of digital economy and institutional quality on economic growth of Bangladesh, Ethiopia, Kenya, and Nigeria. The study adopts the feasible generalized least square method with annual panel data from 1985 to 2017. Results show that digital economy, human capital and knowledge worker, and democratic accountability promote economic growth, while corruption, socioeconomic conditions, and bureaucratic quality retard economic growth. Furthermore, interaction of digital economy with corruption promotes growth. However, the interaction of digital economy with institutional quality retards economic growth, which could be due to the deteriorating institutional quality and low level of economic digitalization in …

Food Price And Inflation Adjustments In Nigeria: Evidence From Threshold Cointegration, Usman A. Bello, Aliyu R. Sanusi

CBN Journal of Applied Statistics (JAS)

This paper investigates two stages of transmission through which inflation stabilization policy affects headline inflation by estimating a threshold cointegration model. The paper finds that asymmetric monetary shocks passing-through food prices exerts inflationary pressure on consumer prices, and is characterized by deep asymmetric movement, large degree of stickiness in adjusting downward, while exhibiting upward momentum in correcting food price fall. In addition, asymmetries were found in consumer price adjustment as food price shock transmits substantial inflationary pressure to consumer prices, while disinflationary effect originating from a fall in food price is inconsequential. The coefficients of adjustment were found to be …

Dynamic Effect Of Exchange Rate Gap Shocks On Stock Market Deepening: Evidence From Nigeria, Kareem Abidemi Arikewuyo

CBN Journal of Applied Statistics (JAS)

The study examines the exchange rate gap shock–stock market deepening nexus in Nigeria using the structural VAR-X (SVAR-X) technique for the period 1986Q1 to 2018Q4. Findings reveal that exchange rate gap shock has a negative but statistically not significant effect on stock market deepening in Nigeria. It was also found that exchange rate passed–through interest rate from second to thirteen quarter, and further through financial openness whose effect, like exchange rate gap, was negative. This implies that exchange rate gap is significantly and negatively related to interest rate and financial openness in Nigeria. It is therefore recommended that the monetary …

Modelling The Impact Of Government Expenditure On Economic Growth In Nigeria: The Moderating Effects Of Oil And Non-Oil Revenue, Victor U. Ijirshar, Gaius M. Asombo, Florence D. Bundepuun, Ashifa Tersugh, Ayila Ngutsav

CBN Journal of Applied Statistics (JAS)

This study examines the relationship between government expenditure and economic growth and assesses the moderating effects of oil revenue and non-oil revenue in Nigeria from 1981 to 2021. The study uncovered short-term asymmetry in the government expenditure-economic growth nexus while the long-term relationship was symmetric. The study found that government expenditure is a significant determinant of economic growth in Nigeria and that oil and non-oil revenue influences the nexus between government expenditure and economic growth in Nigeria positively. The study recommends efficient management of oil revenue, directing investments during high revenue periods and ensuring fiscal sustainability. Government should also establish …

Improving The Efficiency Of Exponential Ratio-Type Estimator For Population Median: A Calibration Weight Adjustment Approach, Mathew J. Iseh, Kufre J. Bassey

CBN Journal of Applied Statistics (JAS)

This paper modifies the Bahl and Tuteja exponential ratio-type estimator for population median under simple random and stratified sampling schemes using calibration weight adjustment technique with supplementary information to vary the stratum weights. The bias and mean square error of the modified estimator were obtained up to the second-order approximation, which satisfies the necessary conditions for efficiency. The findings show that the new estimator surpasses existing estimators in efficiency gain. This suggests the appropriateness of calibration weight modification in boosting the efficiency of a population parameter estimator under stratified random sampling especially where the population parameter of the auxiliary variable …

Stake Size And Wagering In A Professional Betting Environment – When Data Affects Decision Making, Anthony Bedford, Tristan Barnett

International Conference on Gambling & Risk Taking

In this work, we discuss the structure of a number of professional wagering organisations, and how they attempt to deal with the “Ender’s Game” effect – when knowledge of the true nature of the ‘war being wagered’ may have affected the process and choice of betting. We analyse the responses from professional wagering and betting organisations, whom operate predominately in Horseracing and sportsbetting, and they identify the importance of separation of decisions around choices to make and the stakes and size of wagers that are linked to the decisions. The proposed model, practically carried out by one company, is an …

Analytical Approach For Monitoring The Behavior Of Patients With Pancreatic Adenocarcinoma At Different Stages As A Function Of Time, Aditya Chakaborty Dr, Chris P. Tsokos Dr

Biology and Medicine Through Mathematics Conference

No abstract provided.

Quantifying The Effect Of Socio-Economic Predictors And The Built Environment On Mental Health Events In Little Rock, Ar, Alfieri Ek, Grant Drawve, Samantha Robinson, Jyotishka Datta

Sociology and Criminology Faculty Publications and Presentations

Law enforcement agencies continue to grow in the use of spatial analysis to assist in identifying patterns of outcomes. Despite the critical nature of proper resource allocation for mental health incidents, there has been little progress in statistical modeling of the geo-spatial nature of mental health events in Little Rock, Arkansas. In this article, we provide insights into the spatial nature of mental health data from Little Rock, Arkansas between 2015 and 2018, under a supervised spatial modeling framework. We provide evidence of spatial clustering and identify the important features influencing such heterogeneity via a spatially informed hierarchy of generalized …

A Monte Carlo Analysis Of Nonprobability Sampling & Post Hoc Corrections, Julia Hong

Masters Theses & Specialist Projects

Nonprobability samples are often used in place of probability samples because the former are less trouble and less expensive. Unfortunately, it is difficult to determine how well a sample represents population parameters when using nonprobability samples. Researchers attempt to mitigate the disadvantages of nonprobability sampling by performing post hoc corrections, but this adjustment may not successfully undo the effects of nonprobability sampling. To examine these effects, a Monte Carlo simulation was conducted to create a pseudo-population from which samples were drawn. Forty-one conditions were replicated 10,000 times each, with each sample consisting of 100 observations. A post-stratification adjustment was made …

Two Sample Statistical Test For Location Parameters, Narinder Kumar, Arun Kumar

Journal of Modern Applied Statistical Methods

A class of distribution-free tests for the homogeneity of location parameters is proposed and compared with different competitors in terms of Pitman asymptotic relative efficiency. A numerical example is provided and a simulation study is made to check the performance of the tests.