Statistics and Probability Commons^™

Playfair's Introduction Of Time Series To Represent Data, Diana White, Joshua Eastes, Negar Janani, River Bond

Statistics and Probability

No abstract provided.

Playfair's Novel Visual Displays Of Data, Diana White, River Bond, Joshua Eastes, Negar Janani

Statistics and Probability

No abstract provided.

Two Pens In A Pocket Must Be Different: A Nerd-Oriented Lesson From Statistics, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Some people always carry a pen with them, so that if an idea comes to mind, they will always be able to write it down. Pens sometimes run out of ink. So, just in case, people carry two pens. The problem is that often, when one carries two identical pens, they seem to run out of ink at about the same time -- which defeats the whole purpose of carrying two pens. In this paper, we provide a simple statistics-based explanation of this phenomenon, and show that a seemingly natural idea of carrying three pens will not help. The only …

Working Children On Java Island 2017, Yuniarti

English Language Institute

Children's wellbeing has currently become a global concern as many of them are engaged in the labor force. A small area estimation (SAE) technique, EBLUP under Fey Herriot model, is employed to reveal their number in regencies of Java Island. Statistics have been disaggregated by geographical location (urban/rural) and gender. These statistics are required by the government as the basis for policy making.

Harmony Amid Chaos, Drew Schaffner

Pence-Boyce STEM Student Scholarship

We provide a brief but intuitive study on the subjects from which Galois Fields have emerged and split our study up into two categories: harmony and chaos. Specifically, we study finite fields with elements where is prime. Such a finite field can be defined through a logarithm table. The Harmony Section is where we provide three proofs about the overall symmetry and structure of the Galois Field as well as several observations about the order within a given table. In the Chaos Section we make two attempts to analyze the tables, the first by methods used by Vladimir Arnold as …

Models For Data Analysis In Accelerated Reliability Growth, Cesar Alexander Ruiz Torres

Graduate Theses and Dissertations

This work develops new methodologies for analyzing accelerated testing data in the context of a reliability growth program for a complex multi-component system. Each component has multiple failure modes and the growth program consists of multiple test-fix stages with corrective actions applied at the end of each stage. The first group of methods considers time-to-failure data and test covariates for predicting the final reliability of the system. The time-to-failure of each failure mode is assumed to follow a Weibull distribution with rate parameter proportional to an acceleration factor. Acceleration factors are specific to each failure mode and test covariates. We …

Mathematical Modeling: Instructor And Student Resources, Marnie Phipps, Patty Wagner

Mathematics Ancillary Materials

This collection of student and instructor materials for Mathematical Modeling contains lesson plans, lecture slides, homework, learning goals, and student notes for the following major topics:

• Linear Functions
• Quadratic Functions
• Exponential Functions
• Logarithmic Functions

This is a materials update for a collection of materials created for a Round Nine ALG Textbook Transformation Grant.

Applications Of Portable Libs For Actinide Analysis, Ashwin P. Rao, John D. Auxier Ii, Dung Vu, Michael B. Shattan

Faculty Publications

A portable LIBS device was used for rapid elemental impurity analysis of plutonium alloys. This device demonstrates the potential for fast, accurate in-situ chemical analysis and could significantly reduce the fabrication time of plutonium alloys.

Measuring Sexual Excitation And Sexual Inhibition In A Dutch-Speaking Sample, Malachi Willis

Graduate Theses and Dissertations

Background: Individual differences in sexual excitation and sexual inhibition are important predictors of sexual functioning. Psychometric instruments for these aspects of sexual response were originally developed separately for men (Sexual Inhibition /Sexual Excitation Scales [SIS/SES]) and women (Sexual Excitation/Sexual Inhibition Inventory for Women [SESII-W]). These measures were then adapted to function similarly in samples comprising both men and women (Sexual Inhibition/Sexual Excitation Scales-Short Form [SIS/SES-SF] and Sexual Excitation/Sexual Inhibition Inventory for Women and Men [SESII-W/M], respectively). No published study to our knowledge has administered the SIS/SES and SESII-W/M questionnaires to a sample of both women and men. In the present …

Learning Networks With Categorical Data Using Distance Correlation, And A Novel Graph-Based Multivariate Test, Jian Tinker

Graduate Theses and Dissertations

We study the use of distance correlation for statistical inference on categorical data, especially the induction of probability networks. Szekely et al. first defined distance correlation for continuous variables in [42], and Zhang translated the concept into the categorical setting in [57] by defining dCor(X,Y) for categorical variables X = (x1,...,xI) and Y = (y1,...,yJ) where P(X=xi)=[pi]i and P(Y=yi)=[pi]j with the formula [Please open the document]

Part I of the dissertation covers the background we need to understand this formula, and prepares us to analyze the properties and performance of its applications.

Part II then presents the main results of …

Structural Analysis Of The Multifunctional Spoiie Regulatory Protein Of Clostridioides Difficile., Blythe Emily Bunkers

Graduate Theses and Dissertations

Clostridioides (formally Clostridium) difficile is a medically relevant pathogen pertinent to infectious disease research. C. difficile is distinctly known for its ability to produce two toxins, enterotoxin A and cytotoxin B, and the propensity to colonize the mammalian gastrointestinal tract. It is known that metabolism is tightly correlated with sporulation in endospore producers such as C. difficile, but an interesting and novel regulatory relationship found by the Ivey lab has yet to be understood. The relationship explored in this study is observed between the sporulation factor, SpoIIE, which represses expression of an ABC peptide transporter, app. In this study, two …

Network-Based Statistical Analysis Of Functional Magnetic Resonance Imaging Data From Aphasia Patients, Xingpei Zhao

Theses and Dissertations

Functional magnetic resonance imaging (fMRI) is a neuroimaging technique that provides insight into brain function and activity. Network models of fMRI signals can reveal functional connectivity related to certain brain disorders, such as post-stroke aphasia. This thesis aims to identify the functional connections that distinguish anomic and Broca’s aphasia by comparing the resting-state fMRI from the patients with these two types of aphasia. The network-based statistic (NBS) approach is used to detect such connections. After the analytic pipeline is applied to the fMRI data, the NBS approach identifies a distinct subnetwork between the two types of aphasia, which involves the …

Effect Of Predictor Dependence On Variable Selection For Linear And Log-Linear Regression, Apu Chandra Das

Graduate Theses and Dissertations

We propose a Bayesian approach to the Dirichlet-Multinomial (DM) regression model, which uses horseshoe, Laplace, and horseshoe plus priors for shrinkage and selection. The Dirichlet-Multinomial model can be used to find the significant association between a set of available covariates and taxa for a microbiome sample. We incorporate the covariates in a log-linear regression framework. We design a simulation study to make a comparison among the performance of the three shrinkage priors in terms of estimation accuracy and the ability to detect true signals. Our results have clearly separated the performance of the three priors and indicated that the horseshoe …

Italian Sociologists: A Community Of Disconnected Groups, Aliakbar Akbaritabar, Vincent Traag, Alberto Caimo, Flaminio Squazzoni

Articles

Examining coauthorship networks is key to study scientific collaboration patterns and structural characteristics of scientific communities. Here, we studied coauthorship networks of sociologists in Italy, using temporal and multi-level quantitative analysis. By looking at publications indexed in Scopus, we detected research communities among Italian sociologists. We found that Italian sociologists are fractured in many disconnected groups. The giant connected component of the Italian sociology could be split into five main groups with a mixture of three main disciplinary topics: sociology of culture and communication (present in two groups), economic sociology (present in three groups) and general sociology (present in three …

Combining Machine Learning And Empirical Engineering Methods Towards Improving Oil Production Forecasting, Andrew J. Allen

Master's Theses

Current methods of production forecasting such as decline curve analysis (DCA) or numerical simulation require years of historical production data, and their accuracy is limited by the choice of model parameters. Unconventional resources have proven challenging to apply traditional methods of production forecasting because they lack long production histories and have extremely variable model parameters. This research proposes a data-driven alternative to reservoir simulation and production forecasting techniques. We create a proxy-well model for predicting cumulative oil production by selecting statistically significant well completion parameters and reservoir information as independent predictor variables in regression-based models. Then, principal component analysis (PCA) …

A Review Study Of Functional Autoregressive Models With Application To Energy Forecasting, Ying Chen, Thorsten Koch, Kian Guan Lim, Xiaofei Xu, Nazgul Zakiyeva

Research Collection Lee Kong Chian School Of Business

In this data‐rich era, it is essential to develop advanced techniques to analyze and understand large amounts of data and extract the underlying information in a flexible way. We provide a review study on the state‐of‐the‐art statistical time series models for univariate and multivariate functional data with serial dependence. In particular, we review functional autoregressive (FAR) models and their variations under different scenarios. The models include the classic FAR model under stationarity; the FARX and pFAR model dealing with multiple exogenous functional variables and large‐scale mixed‐type exogenous variables; the vector FAR model and common functional principal component technique to handle …

Assessing Differential Item Functioning In The Perceived Stress Scale, Nana Amma Berko Asamoah

Graduate Theses and Dissertations

When an item on a test functions differently for subgroups of respondents with respect to an exogenous variable (or covariate) after conditioning on the latent variable of interest, the item is said to exhibit Differential Item Functioning (DIF). The 10-item Perceived Stress Scale (PSS10) is administered to respondents via MTurk to quantify “perceived stress” and identify if items on the scale function differently for specific subgroups defined by age, sex, race, marital status, number of children, employment status and social media usage.

The purpose of this study was to compare traditional DIF detection approaches (Mantel-Haenszel, logistic regression, likelihood ratio test …

High-Dimensional Inference Based On The Leave-One-Covariate-Out Regularization Path, Xiangyang Cao

Theses and Dissertations

The increasingly rapid emergence of high dimensional data, where the number of variables p may be larger than the sample size n, has necessitated the development of new statistical methodologies. LASSO and variants of LASSO are proposed and have been the most popular estimators for the high dimensional regression models. However, not much work has focused on analyzing and summarizing the information contained in the entire solution path of the LASSO. This dissertation consists of three research projects that propose and extend the Leave-One-Covariate-Out(LOCO) solution path statistic to regression and graphical models.

In the first chapter, we propose a new …

Next-Term Grade Prediction: A Machine Learning Approach, Audrey Tedja Widjaja, Lei Wang, Nghia Truong Trong, Aldy Gunawan, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

As students progress in their university programs, they have to face many course choices. It is important for them to receive guidance based on not only their interest, but also the "predicted" course performance so as to improve learning experience and optimise academic performance. In this paper, we propose the next-term grade prediction task as a useful course selection guidance. We propose a machine learning framework to predict course grades in a specific program term using the historical student-course data. In this framework, we develop the prediction model using Factorization Machine (FM) and Long Short Term Memory combined with FM …

The Practical Advantages And Disadvantages Of Laplace Regression As An Alternative To Cox Proportional Hazards Model: A Comparison Via Simulation, Sydney Smith

Theses and Dissertations

The Cox proportional hazards model is the most common regression technique for survival analysis. However, the proportional hazards assumption restricts it’s use to a limited group of multiplicative models. Laplace regression is a flexible quantile regression technique for censored observations that is appropriate in a wider variety of applications as compared to the Cox proportional hazards model. Instead of estimating a hazard ratio, Laplace regression which is free from a proportionality assumption, can be used to estimate many adjusted percentiles of survival time allowing for a more complete description of the association of interest. This paper compares the performance of …