Statistics and Probability Commons^™

A Grammar For Reproducible And Painless Extract-Transform-Load Operations On Medium Data, Benjamin S. Baumer

Statistical and Data Sciences: Faculty Publications

Many interesting datasets available on the Internet are of a medium size—too big to fit into a personal computer’s memory, but not so large that they would not fit comfortably on its hard disk. In the coming years, datasets of this magnitude will inform vital research in a wide array of application domains. However, due to a variety of constraints they are cumbersome to ingest, wrangle, analyze, and share in a reproducible fashion. These obstructions hamper thorough peer-review and thus disrupt the forward progress of science. We propose a predictable and pipeable framework for R (the state-of-the-art statistical computing environment) …

Incorporating Pathway Information Into Feature Selection Towards Better Performed Gene Signatures, Suyan Tian, Chi Wang, Bing Wang

Biostatistics Faculty Publications

To analyze gene expression data with sophisticated grouping structures and to extract hidden patterns from such data, feature selection is of critical importance. It is well known that genes do not function in isolation but rather work together within various metabolic, regulatory, and signaling pathways. If the biological knowledge contained within these pathways is taken into account, the resulting method is a pathway-based algorithm. Studies have demonstrated that a pathway-based method usually outperforms its gene-based counterpart in which no biological knowledge is considered. In this article, a pathway-based feature selection is firstly divided into three major categories, namely, pathway-level selection, …

The Housing Bubble, Shelby Brown

Mathematics Senior Capstone Papers

The housing market is constantly changing. Fluctuating housing prices and a flooded market have home buyers hesitant to commit and sellers on edge. What if the prospective buyer or seller could take this financial step already knowing the state of the market? The purpose of this project is to attempt to predict the next housing bubble. A multivariable regression analysis is conducted using relevant data including variables such as average property prices, number of foreclosures, etc. in the United States beginning in the year 2009. The trends, patterns, and models created from the regression analysis are compared against data models …

Angry Birds Fly High Again With Data Analytics, Singapore Management University

Perspectives@SMU

User feedback has transformed Rovio’s culture and game design

Historical Study Of The Relationship Between The Federal Funds Rate And The Inflation Rate, Aaron Wilkins

Undergraduate External Publications

It is believed that in order to control high inflation rates, the Federal Reserve Bank (“the Fed”) increases the federal funds rate and when the inflation rate gets low, the Fed takes the opposite approach. (The federal funds rate is a rate of interest that banks charge each other to lend funds and stay above the reserve requirement, set by the government.) This project examines the relationship between the federal funds rate and the inflation rate. Sixty-five years of historical inflation rates and federal funds rates were used as the basis for this exploration. Because a time lag between the …

The Evolution Of Data Science: A New Mode Of Knowledge Production, Jennifer Lewis Priestley, Robert J. Mcgrath

Faculty Articles

Is data science a new field of study or simply an extension or specialization of a discipline that already exists, such as statistics, computer science, or mathematics? This article explores the evolution of data science as a potentially new academic discipline, which has evolved as a function of new problem sets that established disciplines have been ill-prepared to address. The authors find that this newly-evolved discipline can be viewed through the lens of a new mode of knowledge production and is characterized by transdisciplinarity collaboration with the private sector and increased accountability. Lessons from this evolution can inform knowledge production …

Measuring Birth Trauma Rates In Maine Using Public Data, Mike Lapika

Thinking Matters Symposium Archive

An increasing number of states are creating databases that collect and organize health insurance claims from public and private health care payers. Since December 2016, at least 18 states have these “all-payer claims databases” (APCDs), including Maine. APCDs are intended to inform cost containment and quality improvement by increasing transparency and informing consumer choice. For this project, we assessed how Maine’s APCD data might be used to produce standardized quality measures across facilities in the state. Specifically, we tested a birth outcome quality measure developed by the Agency for Healthcare Research and Quality (AHRQ), Birth Trauma – Injury to Neonate …

Dice Mythbusters, C. Warren Campbell, William P. Dolan

Student Research Conference Select Presentations

All dice are unfair because they cannot be manufactured with absolute precision. However, some dice are more unfair than others. Each year hundreds of millions of dice are sold worldwide. Dice commonly used in role playing games are 4-sided (D4), 6-sided (D6), 8-sided (D8), 10-sided (D10), 12-sided (D12), and 20-sided (D20). Most of these are manufactured using plastic mold injection and rock tumbler methods. This method can result in dimensional inaccuracies in the dice and sometimes density inhomogeneities. In 3000-roll tests of eleven D20 dice only three tested fair. In a running chi square test it was shown that for …

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 …

Beach Composition Preferences For Nesting Populations Of Leatherback Sea Turtles (Dermochelys Coriacea), Armila Beach, Guna Yala Comarca, Scott Campbell

Independent Study Project (ISP) Collection

Sea turtles play a critical role in marine ecosystems all over the world, including the Caribbean Sea. However, many sea turtle species are under threat due to anthropogenic impacts, such as habitat destruction and fisheries bycatch. This has caused significant declines in sea turtle populations around the world, which in turn has impacted marine ecosystems where sea turtles play critical roles in proper ecosystem functioning. A crucial part of the sea turtle life cycle that has been threatened by anthropogenic factors is nesting. Sea turtles rely on unspoiled beaches with particular physical characteristics for laying their eggs. One of the …

Avian Upsloping In The Tropics: Myioborus Miniatus And Myioborus Torquatus Abundance In Different Altitudinal Ranges In Boquete, Chiriquí, Panama, Julie Yoon

Independent Study Project (ISP) Collection

Direct and indirect effects of warming global temperatures due to climate change are known to cause upwards shifts of the altitudinal ranges of some avian species. Most susceptible to this trend and at risk of riding the “escalator to extinction” are endemic species in tropical montane cloud forests, such as Myioborus torquatus. There are abiotic factors, like temperature, and biotic interactions, such as the presence of its altitudinal neighbor Myioborus miniatus, that limit the altitudinal range of this bird species in the Neotropics. This study measured abundance of M. miniatus and M. torquatus populations at different altitudinal ranges by point …

A Survey Of Beetle Diversity (Order Coleoptera) On Lizard Island, John Mccormack

Independent Study Project (ISP) Collection

The beetles (order Coleoptera) of Lizard Island, a small granitic island on the mid shelf of the Great Barrier Reef, have never been assessed in the scientific literature. Prior to our work, only a single beetle genus had been documented on the island (Caryotrypes Decelle, 1968), based on a single specimen collected in 1993 (Reid & Beatson 2013). We conducted a survey of Lizard Island in April 2019 to determine which beetle families are present on the island and which families are the most diverse. The survey also assessed the beetle diversity in different habitats on the island and two …

Rates Of Relative Sea Level Rise Along The United States East Coast, Jesse N. Beckman, Joseph E. Garcia

Virginia Journal of Science

Recent studies have indicated that some coastal areas, including the East Coast of the United States, are experiencing higher rates of sea level rise than the global average. Rates of relative sea level rise are affected by changes in ocean dynamics, as well as by surface elevation fluctuations due to local land subsidence or uplift. In this study, we derived long-term trends in annual mean relative sea level using tide gauge data obtained from the Permanent Service for Mean Sea Level for stations along the United States East Coast. Stations were grouped by location into the Northeast, Mid-Atlantic, and Southeast …

Accurate Inference For Repeated Measures In High Dimensions, Xiaoli Kong, Solomon W. Harrar

Mathematics and Statistics: Faculty Publications and Other Works

This paper proposes inferential methods for high-dimensional repeated measures in factorial designs. High-dimensional refers to the situation where the dimension is growing with sample size such that either one could be larger than the other. The most important contribution relates to high-accuracy of the methods in the sense that p-values, for example, are accurate up to the second-order. Second-order accuracy in sample size as well as dimension is achieved by obtaining asymptotic expansion of the distribution of the test statistics, and estimation of the parameters of the approximate distribution with second-order consistency. The methods are presented in a unified and …

Daily And Seasonal Variability Of Offshore Wind Power On The Central California Coast And Statewide Demand, Matthew Douglas Kehrli

Physics

No abstract provided.

Efficient Class Of Estimators For Finite Population Mean Using Auxiliary Information In Two-Occasion Successive Sampling, G. N. Singh, Mohd Khalid

Journal of Modern Applied Statistical Methods

In the case of sampling on two occasions, a class of estimators is considered which uses information on the first occasion as well as the second occasion in order to estimate the population means on the current (second) occasion. The usefulness of auxiliary information in enhancing the efficiency of this estimation is examined through the class of proposed estimators. Some properties of the class of estimators and a strategy of optimum replacement are discussed. The proposed class of estimators were empirically compared with the sample mean estimator in the case of no matching. The established optimum estimator, which is a …

A Data-Driven Approach For Modeling Agents, Hamdi Kavak

Computational Modeling & Simulation Engineering Theses & Dissertations

Agents are commonly created on a set of simple rules driven by theories, hypotheses, and assumptions. Such modeling premise has limited use of real-world data and is challenged when modeling real-world systems due to the lack of empirical grounding. Simultaneously, the last decade has witnessed the production and availability of large-scale data from various sensors that carry behavioral signals. These data sources have the potential to change the way we create agent-based models; from simple rules to driven by data. Despite this opportunity, the literature has neglected to offer a modeling approach to generate granular agent behaviors from data, creating …

Latent Choice Models To Account For Misclassification Errors In Discrete Transportation Data, Lacramioara Elena Balan

Civil & Environmental Engineering Theses & Dissertations

One of the most fundamental tasks when it comes to analyzing data using statistical methods is to understand the relationship between the explanatory variables and the outcome. Misclassification of explanatory variables is a common risk when using statistical modeling techniques. In this dissertation, we define ‘misclassification,’ as a response that is reported or recorded in the wrong category; for example, a variable is registered as a one when it should have the value zero. Misclassification can easily happen in any data; for example, in an interview setting where the respondent misunderstands the question or the interviewer checks the wrong box. …

Spatio-Temporal Cluster Detection And Local Moran Statistics Of Point Processes, Jennifer L. Matthews

Mathematics & Statistics Theses & Dissertations

Moran's index is a statistic that measures spatial dependence, quantifying the degree of dispersion or clustering of point processes and events in some location/area. Recognizing that a single Moran's index may not give a sufficient summary of the spatial autocorrelation measure, a local indicator of spatial association (LISA) has gained popularity. Accordingly, we propose extending LISAs to time after partitioning the area and computing a Moran-type statistic for each subarea. Patterns between the local neighbors are unveiled that would not otherwise be apparent. We consider the measures of Moran statistics while incorporating a time factor under simulated multilevel Palm distribution, …

Disparities In Sentencing: The Impact Of Race, Gender And Mental Health, Briana Paige

Sociology & Criminal Justice Theses & Dissertations

The purpose of this study is to examine the effect that race and mental health play on sentence length in the United States. Mentally ill people are gradually being confined in prisons across the United States and there is an absence of literature that looks at the interaction of race and mental health in regards to sentencing. The focal concerns perspective provides the theoretical framework that guides this study. Multiple linear regressions were used to examine both state and federal prison inmates to examine the effect race, mental health and other extra-legal factors play on sentence length. Results show that …

Median Confidence Regions In A Nonparametric Model, Edsel A. Pena, Taeho Kim

Faculty Publications

The nonparametric measurement error model (NMEM) postulates that Xi=Δ+ϵi,i=1,2,…,n;Δ∈R with ϵi,i=1,2,…,n, IID from F(⋅)∈Fc,0, where Fc,0 is the class of all continuous distributions with median 0, so Δ is the median parameter of X. This paper deals with the problem of constructing a confidence region (CR) for Δ under the NMEM. Aside from the NMEM, the problem setting also arises in a variety of situations, including inference about the median lifetime of a complex system arising in engineering, reliability, biomedical, and public health settings, as well as in the economic arena such as when dealing with household income. Current methods …

Inflated Standard Errors Of Mcmc Estimates In Irt, Dongho Shin

Theses and Dissertations

Two widely used algorithms for estimating item response theory (IRT) parameters are Markov chain Monte Carlo (MCMC) and the EM algorithm. In general, the MCMC algorithm has advantages over the EM algorithm - for example, the MCMC algorithm allows one to estimate the desired posterior distribution and also works more straightforwardly with complex IRT models. This ease of use, allows one to implement the MCMC algorithm without carefully consideration. Previous studies, Hendrix (2011) and Lee (2016), noted that the estimated standard errors from the MCMC algorithm are larger than those from the EM algorithm. Therefore, this study investigate the reason …

Newsworthy Migrants: Sentiment And Text Analysis Of Dutch Newspapers, Nicholas J. Schmitz

Independent Study Project (ISP) Collection

Understanding how a migrant population is viewed and displayed by the host country has been a struggle for a long period of time for anyone studying migration. Traditional methods of collecting information were tedious, time intensive and expensive. However, Big data has been providing unique solutions to gaps in information in many different fields across the world. Media plays an important part in developing and assessing the public opinion on a topic. With the availability of a large number of online articles from historical time periods, it is possible to use quantitative analysis, such as text analytics, to can see …

Spatio-Temporal Analysis Of Precipitation And Flood Data From South Carolina, Haigang Liu

Theses and Dissertations

Spatio-temporal data are everywhere: we encounter them on TV, in newspapers, on computer screens, on tablets, and on plain paper maps. As a result, researchers in di- verse areas are increasingly faced with the task of modeling geographically-referenced and temporally-correlated data. In this dissertation, we propose two different spa- tiotemporal models to capture the behavior of rainfall and flood data in the state of South Carolina.

Both models are built using a Bayesian hierarchical framework, which involves specifying the true underlying process in the first level and the spatio-temporal ran- dom effect in the second level of the hierarchy. The …

Cluster Analysis Of Mixed-Mode Data, Yawei Liang

Theses and Dissertations

In the modern world, data have become increasingly more complex and often contain different types of features. Two very common types of features are continuous and discrete variables. Clustering mixed-mode data, which include both continuous and discrete variables, can be done in various ways. Furthermore, a continuous variable can take any value between its minimum and maximum. Types of continuous vari- ables include bounded or unbounded normal variables, uniform variables, circular variables, etc. Discrete variables include types other than continuous variables, such as binary variables, categorical (nominal) variables, Poisson variables, etc. Difficulties in clustering mixed-mode data include handling the association …

Enhancing Smes’ Data Analytics Capability Through University Tie-Ups, Gary Pan, Poh Sun Seow, Benjamin Huan Zhou Lee

Research Collection School Of Accountancy

Harnessing the power of data analytics, SMEs can now generate visualisations of the company's historical data to date, and predictions for the future - something which is nearly impossible before the era of big data.

Randomization Analysis Driven Software, Steph-Yves Louis

Theses and Dissertations

The application of a method of randomization for a clinical trial frequently summarizes to using Simple Randomization. Even though the latter method provides favorable characteristics, if the collected sample is not large enough, it still presents the highest chance of imbalance both marginally in the treatment groups and locally in terms of the covariates. Methods of Permuted Block Randomization, Urn Randomization, Stratified Permuted Block Randomization, and Minimization represent popular alternative methods that one should consider depending on the goal of the study. A comparison of the previously mentioned methods is carried to evaluate their performance with samples that are not …

Mle And Bayesian Methods To Analyze Data With Missing Values Below The Limit Of Detection, Xinxin Hu

Theses and Dissertations

As pesticides are widely used in agriculture, more and more people who work at places like farm are exposed to the pesticides. According to enviroment re- searches [Villarejo; 2003; Reigart and Roberts; 1999], being exposed to some kind of pesticides like Organophosphorus (OP) insecticides has significantly effected the health of farmworkers and their family. The actual level of pesticides can be detected with some limitation for now. However, it is hard to detect when the level is below the limit of detection (LOD). Therefore, the goal of our research is to propose several different methods to analyze data …

Regression For Pooled Testing Data With Biomedical Applications, Juexin Lin

Theses and Dissertations

Since first introduced by Dorfman in 1943, pooled testing has been widely used as a cost and time effective testing protocol in the variety of applications. This dis- sertation consists of three projects that reveal the use of pooling techniques in the disease prevention from the perspective of regression. For disease monitoring and control, individual covariates information are often of practical interest and yield meaningful interpretations. It is natural to model the outcome of interest, which can be either a disease status (binary) or a biomarker concentration index (continuous), with individual-specific covariates through a regression analysis. Chapter 2 focuses on …

Fixing Metric Fixation: A Review Of The Tyranny Of Metrics, Donald Roth

Faculty Work Comprehensive List

"We should heed the author’s warning that transparent metrics and scorecards are rarely going to be effective substitutes for institutional trust."

Posting about the book The Tyranny of Metrics from In All Things - an online journal for critical reflection on faith, culture, art, and every ordinary-yet-graced square inch of God’s creation.

https://inallthings.org/fixing-metric-fixation-a-review-of-the-tyranny-of-metrics/