Netsci High: Bringing Agency To Diverse Teens Through The Science Of Connected Systems,
2021
New York Hall of Science
Netsci High: Bringing Agency To Diverse Teens Through The Science Of Connected Systems, Stephen M. Uzzo, Catherine B. Cramer, Hiroki Sayama, Russell Faux
Northeast Journal of Complex Systems (NEJCS)
This paper follows NetSci High, a decade-long initiative to inspire teams of teenage researchers to develop, execute and disseminate original research in network science. The project introduced high school students to the computer-based analysis of networks, and instilled in the participants the habits of mind to deepen inquiry in connected systems and statistics, and to sustain interest in continuing to study and pursue careers in fields involving network analysis. Goals of NetSci High ranged from proximal learning outcomes (e.g., increasing high school student competencies in computing and improving student attitudes toward computing) to highly distal (e.g., preparing students for 21st …
Forecasting Of The Covid-19 Epidemic: A Scientometric Analysis,
2021
Department of Mathematics, Universitas Lampung, Lampung, Indonesia
Forecasting Of The Covid-19 Epidemic: A Scientometric Analysis, Pandri Ferdias, Ansari Saleh Ahmar
Library Philosophy and Practice (e-journal)
This study presented a scientometric analysis of scientific publications with discussions of forecasting and COVID-19. The data of this study were obtained from the Scopus database using the keywords: ( TITLE-ABS-KEY (forecast) AND TITLE-ABS-KEY (covid)) and the data were taken on March 26, 2021. This study was a scientometric study. The data were subsequently analyzed using the VosViewer and Bibliometrix R Package. The results showed that “COVID-19” was the keyword most frequently used by researchers, followed by “forecasting” and “human”. Authors who discussed the topic of forecasting COVID-19 come from 83 different countries/regions, with the most articles sent by authors …
Analyzing Student Experience On Group Work With The Application Of Different Group Allocation Approaches,
2021
California Polytechnic State University, San Luis Obispo
Analyzing Student Experience On Group Work With The Application Of Different Group Allocation Approaches, An Yee Tan
Management and HR
Working as a group can be as challenging as working by oneself. Common issues like ineffective group work, unequal work contribution, and poor communication are believed to be the reasons why many students preferred to work individually. The purpose of this study is to understand if there is a disparity in student experience on group work by implementing different methods of group formation, which are, intentional group formation and random assignment. Topics around team well-being, team communication, and team effectiveness are the main focus of this study. The second emphasis of this study is students’ opinions on whether or not …
Analysis And Publication Profile Of Indonesian Scientific Work In 2020 Based On The Scopus Database,
2021
Universitas Negeri Yogyakarta, Yogyakarta, Indonesia
Analysis And Publication Profile Of Indonesian Scientific Work In 2020 Based On The Scopus Database, Akbar Iskandar, Nico Djundharto Djajasinga, Andi Dirga Noegraha, Erwin Gatot, Ansari Saleh Ahmar
Library Philosophy and Practice (e-journal)
This research was conducted to identify and describe the profile of publications in Indonesia in 2020. This research used the bibliometric methods. The data in this research were collected by searching through the Scopus database with the keywords: AFFILCOUNTRY “Indonesia” and PUBYEAR “2020” with the exception of AFFILCOUNTRY other than “Indonesia”. Data were then analyzed based on author affiliation, subject, document type, source type, source title, and language. The results of the research indicated that the development of Indonesian scientific publications was dominated by article types (50.69%) and conference papers (45.83%) with the subject area of publication dominated by engineering, …
Introduction To Statistics In The Psychological Sciences,
2021
Marymount University
Introduction To Statistics In The Psychological Sciences, Linda R. Cote, Rupa Gordon, Chrislyn E. Randell, Judy Schmitt, Helena Marvin
Open Educational Resources Collection
Introduction to Statistics in the Psychological Sciences provides an accessible introduction to the fundamentals of statistics, and hypothesis testing as need for psychology students. The textbook introduces the fundamentals of statistics, an introduction to hypothesis testing, and t Tests. Related samples, independent samples, analysis of variance, correlations, linear regressions and chi-squares are all covered along with expanded appendices with z, t, F correlation, and a Chi-Square table. The text includes key terms and exercises with answers to odd-numbered exercises.
Psychology students often find statistics courses to be different from their other psychology classes. There are some distinct differences, especially involving …
Sars-Cov-2 Pandemic Analytical Overview With Machine Learning Predictability,
2021
Southern Methodist University
Sars-Cov-2 Pandemic Analytical Overview With Machine Learning Predictability, Anthony Tanaydin, Jingchen Liang, Daniel W. Engels
SMU Data Science Review
Understanding diagnostic tests and examining important features of novel coronavirus (COVID-19) infection are essential steps for controlling the current pandemic of 2020. In this paper, we study the relationship between clinical diagnosis and analytical features of patient blood panels from the US, Mexico, and Brazil. Our analysis confirms that among adults, the risk of severe illness from COVID-19 increases with pre-existing conditions such as diabetes and immunosuppression. Although more than eight months into pandemic, more data have become available to indicate that more young adults were getting infected. In addition, we expand on the definition of COVID-19 test and discuss …
Statistical Modeling Of Positive Peer Support On Longitudinal Adolescent Substance Use,
2021
University of Denver
Statistical Modeling Of Positive Peer Support On Longitudinal Adolescent Substance Use, Kady Rost
Electronic Theses and Dissertations
To evaluate this study’s research question of ”Does the latent construct of Positive Peer Support (PPS) relate to the construct of Adolescent Substance Use (ASU) over time, controlling for neighborhood safety, race, and sex?”, Structural Equation (SEM) and Latent Growth Curve Modeling (LGCM) were used to investigate trajectories. Secondary longitudinal data from Zimmerman (2014) of 604 students enrolled for four consecutive years in public schools located in Flint, Michigan. In the secondary data resource, students who participated were declared “at risk” by GPA. Significant relationships were found in SEM: Positive Peer Support to Adolescent Substance Use, All Control Variables to …
On The Evolution Equation For Modelling The Covid-19 Pandemic,
2021
Technological University Dublin
On The Evolution Equation For Modelling The Covid-19 Pandemic, Jonathan Blackledge
Books/Book chapters
The paper introduces and discusses the evolution equation, and, based exclusively on this equation, considers random walk models for the time series available on the daily confirmed Covid-19 cases for different countries. It is shown that a conventional random walk model is not consistent with the current global pandemic time series data, which exhibits non-ergodic properties. A self-affine random walk field model is investigated, derived from the evolutionary equation for a specified memory function which provides the non-ergodic fields evident in the available Covid-19 data. This is based on using a spectral scaling relationship of the type 1/ωα where ω …
A Unified Approach For Constructing Confidence Intervals And Hypothesis Tests Using H-Function,
2021
Wright State University
A Unified Approach For Constructing Confidence Intervals And Hypothesis Tests Using H-Function, Weizhen Wang
Mathematics and Statistics Faculty Publications
We introduce a general method, named the h-function method, to unify the constructions of level-a exact test and 1-a exact confidence interval. Using this method, any confidence interval is improved as follows: i) an approximate interval, including a point estimator, is modified to an exact interval; ii) an exact interval is refined to be an interval that is a subset of the previous one. Two real datasets are used to illustrate the method.
Fourth Down Decision Making: Challenging The Conservative Nature Of Nfl Coaches,
2021
University of Denver
Fourth Down Decision Making: Challenging The Conservative Nature Of Nfl Coaches, Will Palmquist, Ryan Elmore, Benjamin Williams
DU Undergraduate Research Journal Archive
This thesis analyzes the hypothesis that coaches in the National Football League are often too conservative in their decision making on fourth downs. I used R Studio and NFL play-by-play data to simulate actual football plays and drives according to different fourth down strategies. By measuring expected points per drive over thousands of simulated drives, we are able to evaluate the effectiveness of different fourth down strategies. This research points to a number of conclusions regarding the nature of NFL coaches on fourth downs as well as the complexity of modeling and simulating decision making in a complex sport such …
Statistical Approaches For Estimation And Comparison Of Brain Functional Connectivity,
2021
Virginia Commonwealth University
Statistical Approaches For Estimation And Comparison Of Brain Functional Connectivity, Jifang Zhao
Theses and Dissertations
Drug addiction can lead to many health-related problems and social concerns. Functional connectivity obtained from functional magnetic resonance imaging (fMRI) data promotes a variety of fundamental understandings in such association. Due to its complex correlation structure and large dimensionality, the modeling and analysis of the functional connectivity from neuroimage are challenging. By proposing a spatio-temporal model for multi-subject neuroimage data, we incorporate voxel-level spatio-temporal dependencies of whole-brain measurements to improve the accuracy of statistical inference. To tackle large-scale spatio-temporal neuroimage data, we develop a computationally efficient algorithm to estimate the parameters. Our method is used to identify functional connectivity and …
Investigations Into The Genetics Of Mixed Pathologies In Dementia,
2021
University of Kentucky
Investigations Into The Genetics Of Mixed Pathologies In Dementia, Adam Dugan
Theses and Dissertations--Epidemiology and Biostatistics
Alzheimer’s disease (AD) is an irreversible, progressive brain disorder that leads to a loss of memory and thinking skills. While tremendous progress has been made in our understanding of the genetics underlying AD, currently known genetic variants explain only approximately 30% of the heritable risk of developing AD. One hurdle to AD research is that it can only be definitively diagnosed at autopsy, making cruder, clinic-based diagnoses more common. In recent years, several brain pathologies that mimic AD’s clinical presentation have been identified including brain arteriolosclerosis, hippocampal sclerosis (HS), and, most recently, limbic-predominant age-related TDP-43 encephalopathy (LATE). It has become …
Coloring Permutation-Gain Graphs,
2021
Wright State University - Main Campus
Coloring Permutation-Gain Graphs, Daniel Slilaty
Mathematics and Statistics Faculty Publications
Correspondence colorings of graphs were introduced in 2018by Dvoˇr ́ak and Postle as a generalization of list colorings of graphswhich generalizes ordinary graph coloring. Kim and Ozeki observed thatcorrespondence colorings generalize various notions of signed-graph col-orings which again generalizes ordinary graph colorings. In this notewe state how correspondence colorings generalize Zaslavsky’s notionof gain-graph colorings and then formulate a new coloring theory ofpermutation-gain graphs that sits between gain-graph coloring and cor-respondence colorings. Like Zaslavsky’s gain-graph coloring, our newnotion of coloring permutation-gain graphs has well defined chromaticpolynomials and lifts to colorings of the regular covering graph of apermutation-gain graph
Parametric, Nonparametric, And Semiparametric Linear Regression In Classical And Bayesian Statistical Quality Control,
2021
Virginia Commonwealth University
Parametric, Nonparametric, And Semiparametric Linear Regression In Classical And Bayesian Statistical Quality Control, Chelsea L. Jones
Theses and Dissertations
Statistical process control (SPC) is used in many fields to understand and monitor desired processes, such as manufacturing, public health, and network traffic. SPC is categorized into two phases; in Phase I historical data is used to inform parameter estimates for a statistical model and Phase II implements this statistical model to monitor a live ongoing process. Within both phases, profile monitoring is a method to understand the functional relationship between response and explanatory variables by estimating and tracking its parameters. In profile monitoring, control charts are often used as graphical tools to visually observe process behaviors. We construct a …
Neither “Post-War” Nor Post-Pregnancy Paranoia: How America’S War On Drugs Continues To Perpetuate Disparate Incarceration Outcomes For Pregnant, Substance-Involved Offenders,
2021
Pitzer College
Neither “Post-War” Nor Post-Pregnancy Paranoia: How America’S War On Drugs Continues To Perpetuate Disparate Incarceration Outcomes For Pregnant, Substance-Involved Offenders, Becca S. Zimmerman
Pitzer Senior Theses
This thesis investigates the unique interactions between pregnancy, substance involvement, and race as they relate to the War on Drugs and the hyper-incarceration of women. Using ordinary least square regression analyses and data from the Bureau of Justice Statistics’ 2016 Survey of Prison Inmates, I examine if (and how) pregnancy status, drug use, race, and their interactions influence two length of incarceration outcomes: sentence length and amount of time spent in jail between arrest and imprisonment. The results collectively indicate that pregnancy decreases length of incarceration outcomes for those offenders who are not substance-involved but not evenhandedly -- benefitting white …
Dimension Reduction Techniques In Regression,
2021
University of Kentucky
Dimension Reduction Techniques In Regression, Pei Wang
Theses and Dissertations--Statistics
Because of the advances of modern technology, the size of the collected data nowadays is larger and the structure is more complex. To deal with such kinds of data, sufficient dimension reduction (SDR) and reduced rank (RR) regression are two powerful tools. This dissertation focuses on these two tools and it is composed of three projects. In the first project, we introduce a new SDR method through a novel approach of feature filter to recover the central mean subspace exhaustively along with a method to determine the dimension, two variable selection methods, and extensions to multivariate response and large p …
Information Prioritization: A Comparison Between Utility Maximizers And Probability Matchers,
2021
Claremont Colleges
Information Prioritization: A Comparison Between Utility Maximizers And Probability Matchers, Yusuf Ismaeel
CMC Senior Theses
This thesis examines the differences between probability matchers and utility maximizers in their preferences for information sources in a lab environment. In this paper, we consider the best source of information to be the most connected one. We conducted several linear probability model type regressions along with logit regressions. Furthermore, we also attempted to control and fix any potential misclassifications in classifying the cognitive strategy by using instrumental variables. The results show that utility maximizers will almost always choose the most informed node. Probability matchers, on the other hand, do not exhibit such a behavior as the probability matching strategy …
Classification Of Chess Games: An Exploration Of Classifiers For Anomaly Detection In Chess,
2021
Minnesota State University, Mankato
Classification Of Chess Games: An Exploration Of Classifiers For Anomaly Detection In Chess, Masudul Hoque
All Graduate Theses, Dissertations, and Other Capstone Projects
Chess is a strategy board game with its inception dating back to the 15th century. The Covid-19 pandemic has led to a chess boom online with 95,853,038 chess games being played during January, 2021 on lichess.com. Along with the chess boom, instances of cheating have also become more rampant. Classifications have been used for anomaly detection in different fields and thus it is a natural idea to develop classifiers to detect cheating in chess. However, there are no specific examples of this, and it is difficult to obtain data where cheating has occurred. So, in this paper, we develop 4 …
Addressing The Ecological Fallacy With Lagrangian Inference,
2021
University of Nevada, Las Vegas
Addressing The Ecological Fallacy With Lagrangian Inference, Michael Schwob
Calvert Undergraduate Research Awards
Most epidemiologists elect to use statistical models that use population-level data to make inference on the spread of some virus or disease. This has become commonplace in the fields of epidemiology and biostatistics since most data used to construct and verify epidemic models are recorded at the population-level. Obtaining inference from a population-level model may be beneficial in studying the spread of disease in a homogeneous population, but the use of such models to describe a heterogeneous population results in inadequate inference. The inaccuracy of these models is further amplified when one tries to make individual-level inference from these population-level …
Ensemble Protein Inference Evaluation,
2021
University of Montana, Missoula
Ensemble Protein Inference Evaluation, Kyle Lee Lucke
Graduate Student Theses, Dissertations, & Professional Papers
The Protein inference problem is becoming an increasingly important tool that aids in the characterization of complex proteomes and analysis of complex protein samples. In bottom-up shotgun proteomics experiments the metrics for evaluation (like AUC and calibration error) are based on an often imperfect target-decoy database. These metrics make the inherent assumption that all of the proteins in the target set are present in the sample being analyzed. In general, this is not the case, they are typically a mix of present and absent proteins. To objectively evaluate inference methods, protein standard datasets are used. These datasets are special in …
