Applied Statistics Commons^™

Comparing Elevator Strategies For A Parking Lot, Naveed Arafat

Major Papers

In this paper, we compare elevator strategies for a parking garage. It is assumed that the parking garage has several floors and there is an elevator which can stop on each floor. We begin by considering 4 strategies detailed in page 23. For each strategy, we loop the program 100 times, and get 100 mean values for wait times. Welch's test confirms highly significant differences among the 4 strategies. Repeating the analysis multiple times we see that the best of the 4 strategies is strategy 2, which places the elevator on floor 2 (the median floor) after use.

Excess Zeros Under Gam: Tweedie Or Two-Part?, Xianming Zeng

Major Papers

Positive, right-skewed data with excess zeros are encountered in many real-life situations. Two possible techniques to analyze this type of data are: Two-part models and Tweedie models. The two-part models assume existence of a separate zero generating process, while the Tweedie models are based on distributions that allow mass at zero. The paper aims to present a simulation study to investigate the performance of Generalized Additive Models (GAM) under the distribution of Tweedie and two-part models for such data with excess zero by using MSE (Mean Square Error) and relative bias to compare the performance of both methods. We found …

The "Benfordness" Of Bach Music, Chadrack Bantange, Darby Burgett, Luke Haws, Sybil Prince Nelson

Journal of Humanistic Mathematics

In this paper we analyze the distribution of musical note frequencies in Hertz to see whether they follow the logarithmic Benford distribution. Our results show that the music of Johann Sebastian Bach and Johann Christian Bach is Benford distributed while the computer-generated music is not. We also find that computer-generated music is statistically less Benford distributed than human- composed music.

Math And Democracy, Kimberly A. Roth, Erika L. Ward

Journal of Humanistic Mathematics

Math and Democracy is a math class containing topics such as voting theory, weighted voting, apportionment, and gerrymandering. It was first designed by Erika Ward for math master’s students, mostly educators, but then adapted separately by both Erika Ward and Kim Roth for a general audience of undergraduates. The course contains materials that can be explored in mathematics classes from those for non-majors through graduate students. As such, it serves students from all majors and allows for discussion of fairness, racial justice, and politics while exploring mathematics that non-major students might not otherwise encounter. This article serves as a guide …

Exploring Experimental Design And Multivariate Analysis Techniques For Evaluating Community Structure Of Bacteria In Microbiome Data, Kelsey Karnik

Dissertations and Theses in Statistics

The gut microbiome plays a crucial role in human health, and by working collaboratively with microbiologists, we aim to further our understanding of the human gut and its impact on human health. Promoting a diverse microbiome is emphasized throughout microbiology literature, and involving a statistician in designing experiments to relate gut bacteria and some measured health outcome is crucial for ensuring valid and accurate results. By adopting new experimental design and analysis methods, researchers can begin to gain a deeper understanding of how the genetics of our food affect the composition of taxa within the gut microbiome. This dissertation is …

Sentiment Analysis Before And During The Covid-19 Pandemic, Emily Musgrove

Mathematics Summer Fellows

This study examines the change in connotative language use before and during the Covid-19 pandemic. By analyzing news articles from several major US newspapers, we found that there is a statistically significant correlation between the sentiment of the text and the publication period. Specifically, we document a large, systematic, and statistically significant decline in the overall sentiment of articles published in major news outlets. While our results do not directly gauge the sentiment of the population, our findings have important implications regarding the social responsibility of journalists and media outlets especially in times of crisis.

A Comparison Of Confidence Intervals In State Space Models, Jinyu Du

Statistical Science Theses and Dissertations

This thesis develops general procedures for constructing confidence intervals (CIs) of the error disturbance parameters (standard deviations) and transformations of the error disturbance parameters in time-invariant state space models (ssm). With only a set of observations, estimating individual error disturbance parameters accurately in the presence of other unknown parameters in ssm is a very challenging problem. We attempted to construct four different types of confidence intervals, Wald, likelihood ratio, score, and higher-order asymptotic intervals for both the simple local level model and the general time-invariant state space models (ssm). We show that for a simple local level model, both the …

Addressing The Impact Of Time-Dependent Social Groupings On Animal Survival And Recapture Rates In Mark-Recapture Studies, Alexandru M. Draghici

Electronic Thesis and Dissertation Repository

Mark-recapture (MR) models typically assume that individuals under study have independent survival and recapture outcomes. One such model of interest is known as the Cormack-Jolly-Seber (CJS) model. In this dissertation, we conduct three major research projects focused on studying the impact of violating the independence assumption in MR models along with presenting extensions which relax the independence assumption. In the first project, we conduct a simulation study to address the impact of failing to account for pair-bonded animals having correlated recapture and survival fates on the CJS model. We examined the impact of correlation on the likelihood ratio test (LRT), …

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 …

(R2025) Improving The Lda Linear Discriminant Analysis Method By Eliminating Redundant Variables For The Diagnosis Of Covid-19 Patients, Kianoush Fathi Vajargah, Hamid Mottaghi Golshan, Fazel Badakhshan Farahabadi

Applications and Applied Mathematics: An International Journal (AAM)

Nowadays, with the increase in data production speed, the process of data analysis has faced many problems because this big data is often accompanied by plug-in data and redundant data. Therefore, the use of dimensional methods in the pre-data analysis stage is necessary. In data mining, dimensional reduction is one of the most important steps in data pre-processing. Principal component analysis (PCA) and linear discriminant analysis (LDA) are often used to reduce dimensions in data mining. The LDA method is a monitored and controlled method but the PCA is not controlled method. When the number of samples in classes is …

Data-Optimized Spatial Field Predictions For Robotic Adaptive Sampling: A Gaussian Process Approach, Zachary Nathan

Computer Science Senior Theses

We introduce a framework that combines Gaussian Process models, robotic sensor measurements, and sampling data to predict spatial fields. In this context, a spatial field refers to the distribution of a variable throughout a specific area, such as temperature or pH variations over the surface of a lake. Whereas existing methods tend to analyze only the particular field(s) of interest, our approach optimizes predictions through the effective use of all available data. We validated our framework on several datasets, showing that errors can decline by up to two-thirds through the inclusion of additional colocated measurements. In support of adaptive sampling, …

Statistical Methods To Generate Artificial Slot Floor Data For The Advancement Of Casino Related Research, Courtney Bonner, Anastasia (Stasi) D. Baran, Jason D. Fiege, Saman Muthukumarana

International Conference on Gambling & Risk Taking

Abstract:

A common difficulty when researching gambling topics is the availability of high-quality data sets for development and testing. Due to the high level of secrecy within the gambling industry, if data is obtained for research purposes it is often prohibitively obfuscated, incomplete, or aggregated. Although these data have allowed for advancement in academic work, it leaves both the researchers and readers left wondering about what would be possible if more detailed data sets were available. To mitigate the paucity of data available to researchers, we present a Markov chain-based statistical process for producing artificial event data for a simulated …

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.

Optimizing Tumor Xenograft Experiments Using Bayesian Linear And Nonlinear Mixed Modelling And Reinforcement Learning, Mary Lena Bleile

Statistical Science Theses and Dissertations

Tumor xenograft experiments are a popular tool of cancer biology research. In a typical such experiment, one implants a set of animals with an aliquot of the human tumor of interest, applies various treatments of interest, and observes the subsequent response. Efficient analysis of the data from these experiments is therefore of utmost importance. This dissertation proposes three methods for optimizing cancer treatment and data analysis in the tumor xenograft context. The first of these is applicable to tumor xenograft experiments in general, and the second two seek to optimize the combination of radiotherapy with immunotherapy in the tumor xenograft …

An Application Of The Pagerank Algorithm To Ncaa Football Team Rankings, Morgan Majors

Honors Theses

We investigate the use of Google’s PageRank algorithm to rank sports teams. The PageRank algorithm is used in web searches to return a list of the websites that are of most interest to the user. The structure of the NCAA FBS football schedule is used to construct a network with a similar structure to the world wide web. Parallels are drawn between pages that are linked in the world wide web with the results of a contest between two sports teams. The teams under consideration here are the members of the 2021 Football Bowl Subdivision. We achieve a total ordering …

Movie Recommender System Using Matrix Factorization, Roland Fiagbe

Data Science and Data Mining

Recommendation systems are a popular and beneficial field that can help people make informed decisions automatically. This technique assists users in selecting relevant information from an overwhelming amount of available data. When it comes to movie recommendations, two common methods are collaborative filtering, which compares similarities between users, and content-based filtering, which takes a user’s specific preferences into account. However, our study focuses on the collaborative filtering approach, specifically matrix factorization. Various similarity metrics are used to identify user similarities for recommendation purposes. Our project aims to predict movie ratings for unwatched movies using the MovieLens rating dataset. We developed …

Formula 101 Using 2022 Formula One Season Data To Understand The Race Results, Christopher Garcia, Oliver Lopez

Student Scholar Symposium Abstracts and Posters

The reason why I am interested in Formula One is that my friend showed me what Formula One was all about. It became interesting to see the action of the sport, including the battles the drivers have during the race and how fast they go through a corner. Also, when qualifying comes around, they push their car to the absolute limit to gain a few seconds off their opponents. The drivers only in the top 10 receive points from the winner getting 25 points, the last driver in the top 10 getting 1 point, and those below the top ten …

Examining The Effect Of Word Embeddings And Preprocessing Methods On Fake News Detection, Jessica Hauschild

Dissertations and Theses in Statistics

The words people choose to use hold a lot of power, whether that be in spreading truth or deception. As listeners and readers, we do our best to understand how words are being used. There are many current methods in computer science literature attempting to embed words into numerical information for statistical analyses. Some of these embedding methods, such as Bag of Words, treat words as independent, while others, such as Word2Vec, attempt to gain information about the context of words. It is of interest to compare how well these various methods of translating text into numerical data work specifically …

Small But Mighty: Examing The Utility Of Microstatistics In Modeling Ice Hockey, Matt Palmer

Senior Honors Theses

As research into hockey analytics continues, an increasing number of metrics are being introduced into the knowledge base of the field, creating a need to determine whether various stats are useful or simply add noise to the discussion. This paper examines microstatistics – manually tracked metrics which go beyond the NHL’s publicly released stats – both through the lens of meta-analytics (which attempt to objectively assess how useful a metric is) and modeling game probabilities. Results show that while there is certainly room for improvement in understanding and use of microstats in modeling, the metrics overall represent an area of …