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2019

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Articles 511 - 540 of 596

Full-Text Articles in Statistics and Probability

Generalizability Of Effect Sizes Within Aviation Research: More Samples Are Needed, Rian Mehta, Stephen Rice, Scott Winter, Tyler Spence, Maarten Edwards, Karla Candelaria-Oquendo Jan 2019

Generalizability Of Effect Sizes Within Aviation Research: More Samples Are Needed, Rian Mehta, Stephen Rice, Scott Winter, Tyler Spence, Maarten Edwards, Karla Candelaria-Oquendo

International Journal of Aviation, Aeronautics, and Aerospace

It is often the case that researchers attempt to generalize findings from a single convenience sample to the population. They may also wish to make the claim that the sample effect sizes they discover are reasonably similar to the population parameters. The current study attempts to show that they can be mistaken in this assumption, and that different samples can vary dramatically in effect sizes due to myriad discrepancies, such as demographics, sample size, and random error, among other aspects of the samples. Seven hundred and eighty-one participants were recruited from Amazon’s Mechanical Turk, Florida Institute of Technology, Embry-Riddle Aeronautical …

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Mathematically Modeling The Role Of Triglyceride Production On Leptin Resistance, Yu Zhao, Daniel Burkow, Baojun Song Jan 2019

Mathematically Modeling The Role Of Triglyceride Production On Leptin Resistance, Yu Zhao, Daniel Burkow, Baojun Song

Department of Applied Mathematics and Statistics Faculty Scholarship and Creative Works

Diet-induced obesity is becoming more common all over the world, which is increasing the prevalence of obesity-induced chronic diseases such as diabetes, coronary heart disease, cancer, and sleep apnea. Many experimental results show that obesity is often associated with an elevated concentration of plasma leptin and triglycerides. Triglycerides inhibit the passage of leptin across the blood–brain barrier (BBB) to signal the hypothalamus to suppress appetite. However, it is still not clear how triglyceride concentration affects leptin transport across the BBB and energy balance. In this paper, we propose a novel ordinary differential equations model describing the role of leptin in …

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Composite Nonparametric Tests In High Dimension, Alejandro G. Villasante Tezanos Jan 2019

Composite Nonparametric Tests In High Dimension, Alejandro G. Villasante Tezanos

Theses and Dissertations--Statistics

This dissertation focuses on the problem of making high-dimensional inference for two or more groups. High-dimensional means both the sample size (n) and dimension (p) tend to infinity, possibly at different rates. Classical approaches for group comparisons fail in the high-dimensional situation, in the sense that they have incorrect sizes and low powers. Much has been done in recent years to overcome these problems. However, these recent works make restrictive assumptions in terms of the number of treatments to be compared and/or the distribution of the data. This research aims to (1) propose and investigate refined …

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A Flexible Zero-Inflated Poisson Regression Model, Eric S. Roemmele Jan 2019

A Flexible Zero-Inflated Poisson Regression Model, Eric S. Roemmele

Theses and Dissertations--Statistics

A practical problem often encountered with observed count data is the presence of excess zeros. Zero-inflation in count data can easily be handled by zero-inflated models, which is a two-component mixture of a point mass at zero and a discrete distribution for the count data. In the presence of predictors, zero-inflated Poisson (ZIP) regression models are, perhaps, the most commonly used. However, the fully parametric ZIP regression model could sometimes be restrictive, especially with respect to the mixing proportions. Taking inspiration from some of the recent literature on semiparametric mixtures of regressions models for flexible mixture modeling, we propose a …

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Characterizations Of Certain Recently Introduced Discrete Distributions, Gholamhossein G. Hamedani Jan 2019

Characterizations Of Certain Recently Introduced Discrete Distributions, Gholamhossein G. Hamedani

Mathematics, Statistics and Computer Science Faculty Research and Publications

Characterizations of certain recently introduced discrete distributions are presented to complete, in some way, the works cited in the References.

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Less Is More: Beating The Market With Recurrent Reinforcement Learning, Louis Kurt Bernhard Steinmeister Jan 2019

Less Is More: Beating The Market With Recurrent Reinforcement Learning, Louis Kurt Bernhard Steinmeister

Masters Theses

"Multiple recurrent reinforcement learners were implemented to make trading decisions based on real and freely available macro-economic data. The learning algorithm and different reinforcement functions (the Differential Sharpe Ratio, Differential Downside Deviation Ratio and Returns) were revised and the performances were compared while transaction costs were taken into account. (This is important for practical implementations even though many publications ignore this consideration.) It was assumed that the traders make long-short decisions in the S&P500 with complementary 3-month treasury bill investments. Leveraged positions in the S&P500 were disallowed. Notably, the Differential Sharpe Ratio and the Differential Downside Deviation Ratio are risk …

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Wellness Paradigms In Predicting Stress And Burnout Among Beginning Expatriate Teachers, Kimala Proctor Jan 2019

Wellness Paradigms In Predicting Stress And Burnout Among Beginning Expatriate Teachers, Kimala Proctor

Walden Dissertations and Doctoral Studies

Research indicates that the current teacher shortage is in part due to stress and burnout. A topic that has not been examined is beginning expatriate English medium teachers (EMTs) with 5 years or less of teaching experience in the United Arab Emirates and the relationship between using individualized, self-initiated wellness paradigms and stress, job burnout, and intent to leave the teaching profession. The transactional model of stress and coping, Maslach's multidimensional theory of burnout, and the health promotion model were used to evaluate the moderating effects of the EMTs' burnout and stress levels on their wellness and intent to leave. …

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Cronbach’S Alpha Under Insufficient Effort Responding: An Analytic Approach, Stephen W. Carden, Trevor R. Camper, Nicholas S. Holtzman Jan 2019

Cronbach’S Alpha Under Insufficient Effort Responding: An Analytic Approach, Stephen W. Carden, Trevor R. Camper, Nicholas S. Holtzman

Psychology: Faculty Publications

Surveys commonly suffer from insufficient effort responding (IER). If not accounted for, IER can cause biases and lead to false conclusions. In particular, Cronbach’s alpha has been empirically observed to either deflate or inflate due to IER. This paper will elucidate how IER impacts Cronbach’s alpha in a variety of situations. Previous results concerning internal consistency under mixture models are extended to obtain a characterization of Cronbach’s alpha in terms of item validities, average variances, and average covariances. The characterization is then applied to contaminating distributions representing various types of IER. The discussion will provide commentary on previous simulation-based investigations, …

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Enrollment And Assessment Of A First-Year College Class Social Network For A Controlled Trial Of The Indirect Effect Of A Brief Motivational Intervention, Nancy P. Barnett, Melissa A. Clark, Shannon R. Kenney, Graham Diguiseppi, Matthew K. Meisel, Sara Balestrieri, Miles Q. Ott, John Light Jan 2019

Enrollment And Assessment Of A First-Year College Class Social Network For A Controlled Trial Of The Indirect Effect Of A Brief Motivational Intervention, Nancy P. Barnett, Melissa A. Clark, Shannon R. Kenney, Graham Diguiseppi, Matthew K. Meisel, Sara Balestrieri, Miles Q. Ott, John Light

Statistical and Data Sciences: Faculty Publications

Heavy drinking and its consequences among college students represent a serious public health problem, and peer social networks are a robust predictor of drinking-related risk behaviors. In a recent trial, we administered a Brief Motivational Intervention (BMI) to a small number of first-year college students to assess the indirect effects of the intervention on peers not receiving the intervention. Objectives: To present the research design, describe the methods used to successfully enroll a high proportion of a first-year college class network, and document participant characteristics. Methods: Prior to study enrollment, we consulted with a student advisory group and campus stakeholders …

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The Effect Of Vegetative Structure On Nest-Burrow Selection By The Western Burrowing Owl: Comparing Traditional Methods To Photogrammetry With An Unmanned Aerial System, Dylan J. Steffen Jan 2019

The Effect Of Vegetative Structure On Nest-Burrow Selection By The Western Burrowing Owl: Comparing Traditional Methods To Photogrammetry With An Unmanned Aerial System, Dylan J. Steffen

Master's Theses or Doctor of Nursing Practice

The shortgrass prairie ecoregion in the United States has been reduced to 52% of its historical extent, contributing to reduced habitat for native species. One such species is the Burrowing Owl (Athene cunicularia). The Western Burrowing Owl subspecies (A. c. hypugaea) is listed as a Species of Special Concern in nearly every western and midwestern state, including Kansas where it is designated as a Tier II Species of Greatest Conservation Need. Habitat destruction due to conversion to cropland, increasing use of pesticides, and reduction in burrowing mammal abundance are the primary threats that have led to …

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Mefenamic Acid – Hpmc As Hg Amorphous Solid Dispersions: Dissolution Enhancement Using Hot Melt Extrusion Technology, Ashay Shukla Jan 2019

Mefenamic Acid – Hpmc As Hg Amorphous Solid Dispersions: Dissolution Enhancement Using Hot Melt Extrusion Technology, Ashay Shukla

Electronic Theses and Dissertations

Mefenamic acid, a BCS class II drug, displays high permeability and low solubility, thereby exhibiting a poor dissolution profile. Hence to improve the solubility and dissolution rate of Mefenamic acid, Hot Melt Extrusion (HME) technique was employed. The amorphous solid dispersion matrix exhibited enhanced dissolution with desired release characteristics. Hydroxypropylmethylcellulose acetate succinate (AquaSolve™ HPMC-AS HG) was used as a carrier with the poloxamer (Kolliphor P407). The drug load was varied from 20% to 40% within the blend. Drug and polymers were blended using a twin shell V-blender for 10 minutes and extruded using an 11mm twin-screw co-rotating extruder (ThermoFisher Scientific, …

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Dimensionality And Factorial Invariance Of Religiosity Among Christians And The Religiously Unaffiliated: A Cross-Cultural Analysis Based On The International Social Survey Programme, Carlos Miguel Lemos, Ross Joseph Gore, Ivan Puga-Gonzalez, F. Leron Shults Jan 2019

Dimensionality And Factorial Invariance Of Religiosity Among Christians And The Religiously Unaffiliated: A Cross-Cultural Analysis Based On The International Social Survey Programme, Carlos Miguel Lemos, Ross Joseph Gore, Ivan Puga-Gonzalez, F. Leron Shults

VMASC Publications

We present a study of the dimensionality and factorial invariance of religiosity for 26 countries with a Christian heritage, based on the 1998 and 2008 rounds of the International Social Survey Programme (ISSP) Religion survey, using both exploratory and multi-group confirmatory factor analyses. The results of the exploratory factor analysis showed that three factors, common to Christian and religiously unaffiliated respondents, could be extracted from our initially selected items and suggested the testing of four different three-factor models using multi-group confirmatory factor analysis. For the model with the best fit and measurement invariance properties, we labeled the three resulting factors …

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A Tacticians Guide To Conflict, Vol. 1: Advancing Explanations & Predictions Of Intrastate Conflict, Khaled Eid Jan 2019

A Tacticians Guide To Conflict, Vol. 1: Advancing Explanations & Predictions Of Intrastate Conflict, Khaled Eid

CGU Theses & Dissertations

Intrastate conflict is an ever-evolving problem – causes, explanation, and predictions are increasingly murky as traditional methods of analysis focus on structural issues as precursors of conflict. Often times these theories do not consider the underlying meso and micro dynamics that can provide vital insights into the phenomena. Tactical decision-makers are left using models that rely on highly aggregated, country level data to create proper courses of actions (COAs) to address or predict conflict. The shortcoming is that conflicts morph quite rapidly and structural variables can struggle capture such dynamic changes. To address this some tacticians are using big data …

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Neutrosophic Set Is A Generalization Of Intuitionistic Fuzzy Set, Inconsistent Intuitionistic Fuzzy Set (Picture Fuzzy Set, Ternary Fuzzy Set), Pythagorean Fuzzy Set, Q-Rung Orthopair Fuzzy Set, Spherical Fuzzy Set, And N-Hyperspherical Fuzzy Set, While Neutrosophication Is A Generalization Of Regret Theory, Grey System Theory, And Three-Ways Decision (Revisited), Florentin Smarandache Jan 2019

Neutrosophic Set Is A Generalization Of Intuitionistic Fuzzy Set, Inconsistent Intuitionistic Fuzzy Set (Picture Fuzzy Set, Ternary Fuzzy Set), Pythagorean Fuzzy Set, Q-Rung Orthopair Fuzzy Set, Spherical Fuzzy Set, And N-Hyperspherical Fuzzy Set, While Neutrosophication Is A Generalization Of Regret Theory, Grey System Theory, And Three-Ways Decision (Revisited), Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

In this paper we prove that Neutrosophic Set (NS) is an extension of Intuitionistic Fuzzy Set (IFS) no matter if the sum of single-valued neutrosophic components is < 1, or > 1, or = 1. For the case when the sum of components is 1 (as in IFS), after applying the neutrosophic aggregation operators one gets a different result from that of applying the intuitionistic fuzzy operators, since the intuitionistic fuzzy operators ignore the indeterminacy, while the neutrosophic aggregation operators take into consideration the indeterminacy at the same level as truth-membership and falsehood-nonmembership are taken. NS is also more flexible and effective because it …

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Modeling Correlated Data Via Copulas, Panfeng Liang Jan 2019

Modeling Correlated Data Via Copulas, Panfeng Liang

Open Access Theses & Dissertations

Copulas are widely used to model the dependency structure among components of multi- variate data sets. Elliptical copulas, such as Gaussian copula, are most popular copulas being used since many data sets follow elliptical distributions or meta-elliptical distribu- tions (Fang et al. (2002)). However, today's approaches and software packages require us to assume the specific category, such as Gaussian or Student's T, of the elliptical cop- ula before estimating it. In this Thesis, we will propose a Bayesian method using Markov chain Monte Carlo (MCMC) methods to estimate the density function of elliptical copulas without specifying it is the copula …

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Bayesian Analysis Of Variable-Stress Accelerated Life Testing, Richard Okine Jan 2019

Bayesian Analysis Of Variable-Stress Accelerated Life Testing, Richard Okine

Open Access Theses & Dissertations

Several authors have over the years studied the art of modeling data from accelerated life testing and making inferences from such data. In this study, we consider a continuously varying stress accelerated life testing procedure which is the limiting case of the multiple stress-level discussed by Doksum and H´oyland [1]. We derive the likelihood function for the life distribution of the continuously increasing stress accelerated life testing model and consequently the Fisher's Information Matrix. We propose a Bayesian analysis for this distribution using the Gibbs Sampling Procedure. We conduct simulation studies and real data analysis to demonstrate the efficiency of …

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Application Of Urinary Metabolites For Cancer Detection, Qin Gao Jan 2019

Application Of Urinary Metabolites For Cancer Detection, Qin Gao

Open Access Theses & Dissertations

Prostate cancer (PCa) is the 3rd most common cause of male cancer mortality in the US. Early diagnosis and treatment of PCa will improve the quality of care and reduce mortality. The prostate specific antigen (PSA) is commonly used in the current PCa screening, but its limitation has resulted in an intense search for more reliable biomarkers. Studies showed that dogs could differentiate PCa patients from negative control by sniffing their urine. As the odor profiles are generated by volatile organic compounds (VOCs), the finding suggests that particular VOCs could be linked to PCa, PCa risk levels and other cancers. …

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Confidence Intervals For The Expected P-Value, Emmanuel Kofi Abrefa Jan 2019

Confidence Intervals For The Expected P-Value, Emmanuel Kofi Abrefa

Open Access Theses & Dissertations

The p-value is widely used in many application fields. In common practice, a scientific finding is deemed statistically significant if its resultant p-value is less than a pre-specified significance level, for example α = 0.05, albeit many statistically significant results are not reproducible in new studies. Mixed reasons including misuses, abuses, misunderstanding and misinterpretation arouse intensive debates and conservatives around the p-value from time to time over the years. Yet no reasonable solutions have been proposed. In this research, we make efforts to close the gap by advocating the use of confidence level for the expected p-value p0. This allows …

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Robust Statistical Inference For The Gaussian Distribution, Andrews Tawiah Anum Jan 2019

Robust Statistical Inference For The Gaussian Distribution, Andrews Tawiah Anum

Open Access Theses & Dissertations

The aim of robust statistics is to develop statistical procedures which are not unduly influenced by outliers or observations that are not representative of the underlying "true" data generating process. This thesis focuses on an estimator with this characteristic. The divergence function is introduced in Chapter 2 with the sole aim of taking the function f to be the univariate normal distribution and α - [0, 1]. The estimator fails when we rely on the classic Newton's method to converge to the minimum of the density power divergence (MDPD) function. There is a tendency of such estimator never to approach …

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Forecasting Crashes, Credit Card Default, And Imputation Analysis On Missing Values By The Use Of Neural Networks, Jazmin Quezada Jan 2019

Forecasting Crashes, Credit Card Default, And Imputation Analysis On Missing Values By The Use Of Neural Networks, Jazmin Quezada

Open Access Theses & Dissertations

A neural network is a system of hardware and/or software patterned after the operation of neurons in the human brain. Neural networks,- also called Artificial Neural Networks - are a variety of deep learning technology, which also falls under the umbrella of artificial intelligence, or AI. Recent studies shows that Artificial Neural Network has the highest coefficient of determination (i.e. measure to assess how well a model explains and predicts future outcomes.) in comparison to the K-nearest neighbor classifiers, logistic regression, discriminant analysis, naive Bayesian classifier, and classification trees. In this work, the theoretical description of the neural network methodology …

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On The Performance Of Variable Selection And Classification Via Rank-Based Classifier, Md Showaib Rahman None Sarker Jan 2019

On The Performance Of Variable Selection And Classification Via Rank-Based Classifier, Md Showaib Rahman None Sarker

Open Access Theses & Dissertations

In high-dimensional gene expression data analysis, the accuracy and reliability of cancer classification and selection of important genes play a very crucial role. To identify these important genes and predict future outcomes (tumor vs. non-tumor), various methods have been proposed in the literature. But only few of them take into account correlation patterns and grouping effects among the genes. In this article, we propose a rank-based modification of the popular penalized logistic regression procedure based on a combination of l1 and l2 penalties capable of handling possible correlation among genes in different groups. While the l1 penalty maintains sparsity, the …

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Pre-Service Teachers’ Emerging Views On Educational Equity, Melody Wilson Jan 2019

Pre-Service Teachers’ Emerging Views On Educational Equity, Melody Wilson

Master's Theses and Doctoral Dissertations

An equity-based Statistics course for pre-service mathematics teachers could play a role in the development of pre-service teachers’ equity literacy, encouraging conversations about equity in education and illuminating structural factors that contribute to the educational opportunity gap in the U.S. In the Winter 2019 semester, a faculty team at the author’s university piloted such a course. The course included data explorations dealing with structural inequities by race – one of the most difficult topics to address productively in a teacher preparation course. For the present study, a survey of pre-service teachers’ views on educational equity was administered in a required …

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The Impacts Of Race, Residence, And Prenatal Care On Infant Mortality, Mary Christine Dorley Jan 2019

The Impacts Of Race, Residence, And Prenatal Care On Infant Mortality, Mary Christine Dorley

Walden Dissertations and Doctoral Studies

Tennessee ranks high for infant mortality (IM) in the United States. Despite public health efforts, the IM rate for Blacks is twice that of Whites mimicking what is observed nationally. Several risk factors for IM have been identified; however, it was still unclear how places of residence and prenatal care (PNC) affect IM for Tennesseans. The purpose of this study was to assess the relationship between places of residence (conceptualized by rurality and racial concentration), PNC, and IM among racial groups across Tennessee and to determine if race modified these associations. This was a cross-sectional study using data from the …

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Applying Machine Learning Algorithms For The Analysis Of Biological Sequences And Medical Records, Shaopeng Gu Jan 2019

Applying Machine Learning Algorithms For The Analysis Of Biological Sequences And Medical Records, Shaopeng Gu

Electronic Theses and Dissertations

The modern sequencing technology revolutionizes the genomic research and triggers explosive growth of DNA, RNA, and protein sequences. How to infer the structure and function from biological sequences is a fundamentally important task in genomics and proteomics fields. With the development of statistical and machine learning methods, an integrated and user-friendly tool containing the state-of-the-art data mining methods are needed. Here, we propose SeqFea-Learn, a comprehensive Python pipeline that integrating multiple steps: feature extraction, dimensionality reduction, feature selection, predicting model constructions based on machine learning and deep learning approaches to analyze sequences. We used enhancers, RNA N6- methyladenosine sites and …

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Lack Of Vaccination Risks, Abigail Sebunia Jan 2019

Lack Of Vaccination Risks, Abigail Sebunia

Williams Honors College, Honors Research Projects

This paper is a study regarding how vaccination rates are related to the number of measles cases that occur in a particular state. First, I will review the history of vaccines and the motivations for the refusals of this medical procedure. In addition, I will examine the various regulations regarding vaccinations and which states allow non-medical exemptions for religious or personal reasons. Within my analysis, I will provide examples of recent outbreaks to represent the extent of this current dilemma. Furthermore, I will offer potential solutions to mitigate measles outbreaks and the science regarding Herd Immunity Thresholds (HIT) to limit …

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Effects On Perception And Accuracy Of Live Putting When Leaving The Flagstick In The Hole, Danielle Nicholson Jan 2019

Effects On Perception And Accuracy Of Live Putting When Leaving The Flagstick In The Hole, Danielle Nicholson

Williams Honors College, Honors Research Projects

The purpose of this study was to investigate the preferences of golfers and how those preferences affected their putting. This study involved participants who were golfers with a four-handicap or better taking a survey of their preferences of having the flagstick in and out and then assessing their putting from various distances with the flagstick in and out. The researcher measured the distance of the golf ball away from the hole after it had finished rolling. Then, t-tests were used to compare the data with the flagstick in and flagstick out to determine if there is a significant difference. The …

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Microarray Data Analysis And Classification Of Cancers, Grant Gates Jan 2019

Microarray Data Analysis And Classification Of Cancers, Grant Gates

Williams Honors College, Honors Research Projects

When it comes to cancer, there is no standardized approach for identifying new cancer classes nor is there a standardized approach for assigning cancer tumors to existing classes. These two ideas are known as class discovery and class prediction. For a cancer patient to receive proper treatment, it is important that the type of cancer be accurately identified. For my Senior Honors Project, I would like to use this opportunity to research a topic in bioinformatics. Bioinformatics incorporates a few different subjects into one including biology, computer science and statistics. An intricate method for class discovery and class prediction is …

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A Comparative Study Of Kendall-Theil Sen, Siegel Vs Quantile Regression With Outliers, Ahmad Farooqi Jan 2019

A Comparative Study Of Kendall-Theil Sen, Siegel Vs Quantile Regression With Outliers, Ahmad Farooqi

Wayne State University Dissertations

Researchers in social and behavioral sciences usually interested in study the relationship between a response variable Y_i and one or more independent predictors〖 X〗_i either for the purpose of explanation or prediction. Ordinary Least Square Regression is a parametric approach used to study this kind of relationship. One of the disadvantages of Ordinary Least Square is it does not fit well in the presence of outliers in the response variable Y_i or both in the response variable Y_i and the predictor variable〖 X〗_i, also if the data were sampled from a non-normal distribution. Quantile Regression, Theil-Sen regression, and the modified …

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Reporting Number Needed To Treat In Clinical Trials Published In Physical Therapy Specific Literature 1989 - 2018, Susan Ann Talley Jan 2019

Reporting Number Needed To Treat In Clinical Trials Published In Physical Therapy Specific Literature 1989 - 2018, Susan Ann Talley

Wayne State University Dissertations

Evidence-based practice requires physical therapists to make clinical decisions about the best intervention to use when providing services to patients/clients. Although null hypothesis significance testing (NHST) is frequently used to interpret the outcome of a clinical trial investigating the comparative effectiveness of an intervention, statistical significance does not directly translate into clinical importance. Number needed to treat (NNT) is a measure of effect size (ES) that may be particularly useful when translating the results from clinical trials to PT clinical practice. The purpose of this study was to conduct a bibliometric content analysis of the methods of reporting research results …

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Global Warming Statistical Analysis, Jared Skinner Jan 2019

Global Warming Statistical Analysis, Jared Skinner

Williams Honors College, Honors Research Projects

This paper will investigate global warming and its effects on natural disasters. I will review the historic movements of climate change and activism, as well as the current discussions surrounding global warming. Secondly, I will examine various datasets, paying attention to the severity and frequency of specific natural disasters. I will then touch briefly on the topic of catastrophe modeling as it relates to the increased risk and losses associated with the discussed natural disasters and how those put the problem of global warming in a framework which financial and government institutions can grasp. I will also be analyzing economic …

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