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Introduction To Statistics (Ga Southern), Scott Kersey, Stephen Carden 2018 Georgia Southern University

Introduction To Statistics (Ga Southern), Scott Kersey, Stephen Carden

Mathematics Grants Collections

This Grants Collection for Introduction to Statistics was created under a Round Eight ALG Textbook Transformation Grant.

Affordable Learning Georgia Grants Collections are intended to provide faculty with the frameworks to quickly implement or revise the same materials as a Textbook Transformation Grants team, along with the aims and lessons learned from project teams during the implementation process.

Documents are in .pdf format, with a separate .docx (Word) version available for download. Each collection contains the following materials:

  • Linked Syllabus
  • Initial Proposal
  • Final Report


Multivariate Spectral Analysis Of Crism Data To Characterize The Composition Of Mawrth Vallis, Melissa Luna 2018 Wesleyan University

Multivariate Spectral Analysis Of Crism Data To Characterize The Composition Of Mawrth Vallis, Melissa Luna

Melissa Luna

No abstract provided.


Effect Of Anthropometric Variability On Middle-Market Aircraft Seating, Tara C. Sriram 2018 Embry-Riddle Aeronautical University, Worldwide

Effect Of Anthropometric Variability On Middle-Market Aircraft Seating, Tara C. Sriram

International Journal of Aviation, Aeronautics, and Aerospace

A middle-of-market aircraft, or MoMA, is defined as an aircraft capable of flying 180-250 passengers without refueling for 2,300-5,800 miles(~2,000-5,000 nautical miles). As the name suggests, middle-of-market aircraft are positioned in between the market segments served by narrow body (single-aisle) and wide body (twin-aisle) aircraft. This paper presents the findings of a study on the effect of anthropomorphic variability on economy class seating on middle-market aircraft currently in service. The study found that among 130 middle-market LOPAs, the mean seat pitch was greater for US airlines than for Asian airlines. Furthermore, the sampled Asian airlines ...


Learning And Control Using Gaussian Processes, Achin Jain, Truong X Nghiem, Manfred Morari, Rahul Mangharam 2018 University of Pennsylvania

Learning And Control Using Gaussian Processes, Achin Jain, Truong X Nghiem, Manfred Morari, Rahul Mangharam

Real-Time and Embedded Systems Lab (mLAB)

Building physics-based models of complex physical systems like buildings and chemical plants is extremely cost and time prohibitive for applications such as real-time optimal control, production planning and supply chain logistics. Machine learning algorithms can reduce this cost and time complexity, and are, consequently, more scalable for large-scale physical systems. However, there are many practical challenges that must be addressed before employing machine learning for closed-loop control. This paper proposes the use of Gaussian Processes (GP) for learning control-oriented models: (1) We develop methods for the optimal experiment design (OED) of functional tests to learn models of a physical system ...


Inventing Around Edison’S Lamp Patent: The Role Of Patents In Stimulating Downstream Development And Competition, Ron D. Katznelson, John Howells 2018 Bi-Level Technologies

Inventing Around Edison’S Lamp Patent: The Role Of Patents In Stimulating Downstream Development And Competition, Ron D. Katznelson, John Howells

Ron D. Katznelson

We provide the first detailed empirical study of inventing around patent claims.  The enforcement of Edison’s incandescent lamp patent in 1891-1894 stimulated a surge of patenting. Most of these later patents disclosed inventions around the Edison patent.  Some of these patents introduced important new technology in their own right and became prior art for new fields, indicating that invention around patents contributes to dynamic efficiency.  Contrary to widespread contemporary understanding, the Edison lamp patent did not suppress technological advance in electric lighting.  The market position of General Electric (“GE”), the Edison patent-owner, weakened through the period of this patent ...


Decoupling The Stationary Navier-Stokes-Darcy System With The Beavers-Joseph-Saffman Interface Condition, Yong Cao, Yuchuan Chu, Xiaoming He, Mingzhen Wei 2018 Missouri University of Science and Technology

Decoupling The Stationary Navier-Stokes-Darcy System With The Beavers-Joseph-Saffman Interface Condition, Yong Cao, Yuchuan Chu, Xiaoming He, Mingzhen Wei

Xiaoming He

This paper proposes a domain decomposition method for the coupled stationary Navier-Stokes and Darcy equations with the Beavers-Joseph-Saffman interface condition in order to improve the efficiency of the finite element method. The physical interface conditions are directly utilized to construct the boundary conditions on the interface and then decouple the Navier-Stokes and Darcy equations. Newton iteration will be used to deal with the nonlinear systems. Numerical results are presented to illustrate the features of the proposed method.


A Ten-Year Comparison Of Women Authorship In U.S. Dermatology Literature, 1999 Vs. 2009, Shali Zhang, Ha-Young Kim, Rachel E.S. Hill, Emir Veledar, Suephy C. Chen 2018 Emory University

A Ten-Year Comparison Of Women Authorship In U.S. Dermatology Literature, 1999 Vs. 2009, Shali Zhang, Ha-Young Kim, Rachel E.S. Hill, Emir Veledar, Suephy C. Chen

Emir Veledar

Women are entering medicine at increasing rates, particularly in dermatology. In this study, we compared women’s influence and status in academic dermatology with that of men by examining authorship roles in peer-reviewed dermatology literature.Weexamined the literature in2009 and compared that to10 years prior (1999).Atotal of 1399 articles were reviewed, 594 of whichmet study criteria andwere included in statistical analysis. There was amarked increase in senior female authorship over a decade (22% vs. 38%, p b 0.001). Female first authorship increased as well (41% vs. 51%, p b 0.001). In contrast, changes in male senior and ...


Predicting The Next Us President By Simulating The Electoral College, Boyan Kostadinov 2018 New York City College of Technology, CUNY

Predicting The Next Us President By Simulating The Electoral College, Boyan Kostadinov

Journal of Humanistic Mathematics

We develop a simulation model for predicting the outcome of the US Presidential election based on simulating the distribution of the Electoral College. The simulation model has two parts: (a) estimating the probabilities for a given candidate to win each state and DC, based on state polls, and (b) estimating the probability that a given candidate will win at least 270 electoral votes, and thus win the White House. All simulations are coded using the high-level, open-source programming language R. One of the goals of this paper is to promote computational thinking in any STEM field by illustrating how probabilistic ...


Phase Ii Adaptive Enrichment Design To Determine The Population To Enroll In Phase Iii Trials, By Selecting Thresholds For Baseline Disease Severity, Yu Du, Gary L. Rosner, Michael Rosenblum 2018 Johns Hopkins Bloomberg School of Public Health, Department of Biostatistics

Phase Ii Adaptive Enrichment Design To Determine The Population To Enroll In Phase Iii Trials, By Selecting Thresholds For Baseline Disease Severity, Yu Du, Gary L. Rosner, Michael Rosenblum

Johns Hopkins University, Dept. of Biostatistics Working Papers

We propose and evaluate a two-stage, phase 2, adaptive clinical trial design. Its goal is to determine whether future phase 3 (confirmatory) trials should be conducted, and if so, which population should be enrolled. The population selected for phase 3 enrollment is defined in terms of a disease severity score measured at baseline. We optimize the phase 2 trial design and analysis in a decision theory framework. Our utility function represents a combination of the cost of conducting phase 3 trials and, if the phase 3 trials are successful, the improved health of the future population minus the cost of ...


Optimized Adaptive Enrichment Designs For Multi-Arm Trials: Learning Which Subpopulations Benefit From Different Treatments, Jon Arni Steingrimsson, Joshua Betz, Tiachen Qian, Michael Rosenblum 2018 Department of Biostatistics, Brown School of Public Health

Optimized Adaptive Enrichment Designs For Multi-Arm Trials: Learning Which Subpopulations Benefit From Different Treatments, Jon Arni Steingrimsson, Joshua Betz, Tiachen Qian, Michael Rosenblum

Johns Hopkins University, Dept. of Biostatistics Working Papers

We consider the problem of designing a randomized trial for comparing two treatments versus a common control in two disjoint subpopulations. The subpopulations could be defined in terms of a biomarker or disease severity measured at baseline. The goal is to determine which treatments benefit which subpopulations. We develop a new class of adaptive enrichment designs tailored to solving this problem. Adaptive enrichment designs involve a preplanned rule for modifying enrollment based on accruing data in an ongoing trial. The proposed designs have preplanned rules for stopping accrual of treatment by subpopulation combinations, either for efficacy or futility. The motivation ...


Modeling Mayfly Nymph Length Distribution And Population Dynamics Across A Gradient Of Stream Temperatures And Stream Types, Jeremy Anthony, Jennifer Baccam, Imanuel Bier, Emily Gregg, Leif Halverson, Ryan Mulcahy, Emmanuel Okanla, Samira A. Osman, Adam R. Pancoast, Kevin C. Schultz, Alex Sushko, Jennifer Vorarath, Yia Vue, Austin Wagner, Emily Gaenzle Schilling, John M. Zobitz 2018 Augsburg College

Modeling Mayfly Nymph Length Distribution And Population Dynamics Across A Gradient Of Stream Temperatures And Stream Types, Jeremy Anthony, Jennifer Baccam, Imanuel Bier, Emily Gregg, Leif Halverson, Ryan Mulcahy, Emmanuel Okanla, Samira A. Osman, Adam R. Pancoast, Kevin C. Schultz, Alex Sushko, Jennifer Vorarath, Yia Vue, Austin Wagner, Emily Gaenzle Schilling, John M. Zobitz

Spora: A Journal of Biomathematics

We analyze a process-based temperature model for the length distribution and population over time of mayfly nymphs. Model parameters are estimated using a Markov Chain Monte Carlo parameter estimation method utilizing length distribution data at five different stream sites. Two different models (a standard exponential model and a modified Weibull model) of mayfly mortality are evaluated, where in both cases mayfly length growth is a function of stream temperature. Based on model-data comparisons to the modeled length distribution and the Bayesian Information Criterion, we found that approaches that length distribution data can reliably estimate 2–3 model parameters. Future model ...


Some Applications Of Sophisticated Mathematics To Randomized Computing, Ronald I. Greenberg 2018 Selected Works

Some Applications Of Sophisticated Mathematics To Randomized Computing, Ronald I. Greenberg

Ronald Greenberg

No abstract provided.


Educational Magic Tricks Based On Error-Detection Schemes, Ronald I. Greenberg 2018 Loyola University Chicago

Educational Magic Tricks Based On Error-Detection Schemes, Ronald I. Greenberg

Ronald Greenberg

Magic tricks based on computer science concepts help grab student attention and can motivate them to delve more deeply. Error detection ideas long used by computer scientists provide a rich basis for working magic; probably the most well known trick of this type is one included in the CS Unplugged activities. This paper shows that much more powerful variations of the trick can be performed, some in an unplugged environment and some with computer assistance. Some of the tricks also show off additional concepts in computer science and discrete mathematics.


Models As Weapons: Review Of Weapons Of Math Destruction: How Big Data Increases Inequality And Threatens Democracy By Cathy O’Neil (2016), Samuel L. Tunstall 2018 Michigan State University

Models As Weapons: Review Of Weapons Of Math Destruction: How Big Data Increases Inequality And Threatens Democracy By Cathy O’Neil (2016), Samuel L. Tunstall

Numeracy

Cathy O’Neil. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy (New York, NY: Crown) 272 pp. ISBN 978-0553418811.

Accessible to a wide readership, Cathy O’Neil’s Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy provides a lucid yet alarming account of the extensive reach of mathematical models in influencing all of our lives. With a particular eye towards social justice, O’Neil not only warns modelers to be cognizant of the effects of their work on real people—especially vulnerable groups who have less power to fight back—but also ...


Iterative Matrix Factorization Method For Social Media Data Location Prediction, Natchanon Suaysom 2018 Harvey Mudd College

Iterative Matrix Factorization Method For Social Media Data Location Prediction, Natchanon Suaysom

HMC Senior Theses

Since some of the location of where the users posted their tweets collected by social media company have varied accuracy, and some are missing. We want to use those tweets with highest accuracy to help fill in the data of those tweets with incomplete information. To test our algorithm, we used the sets of social media data from a city, we separated them into training sets, where we know all the information, and the testing sets, where we intentionally pretend to not know the location. One prediction method that was used in (Dukler, Han and Wang, 2016) requires appending one-hot ...


Multi-State Modeling Of Hospital Frequent Users, Yu Liang 2018 University of Windsor

Multi-State Modeling Of Hospital Frequent Users, Yu Liang

Major Papers

The top 1% of frequent users account for 34% of public health system expenditures in Ontario, while the top 5% account for 66%. In this paper, we explore the efficacy of an intervention aimed at reducing hospital utilization for a group of patients defined as frequent users, by using Multi-state modeling. We employ time-homogeneous, time-inhomogeneous, parametric and semi-parametric Markov processes to study the transitions of the patients between hospital, ER and outside during a follow up period of one year. The results do not indicate any strong evidence that the intervention was beneficial.


Queues With Server Utilization Of One, Robert Aidoo 2018 University of Windsor

Queues With Server Utilization Of One, Robert Aidoo

Major Papers

In most queueing systems of type GI/G/1, the stability condition requires that the server utilization be strictly less than 1. The standard exception is a D/D/1 system in which stability still holds for server utilization equal to 1. This paper presents other cases when server utilization can equal 1, and discusses their characteristics.


Modeling The Decline In English Passivization, Liwen Hou, David Smith 2018 Northeastern University

Modeling The Decline In English Passivization, Liwen Hou, David Smith

Proceedings of the Society for Computation in Linguistics

Evidence from the Hansard corpus shows that the passive voice in British English has declined in relative frequency over the last two centuries. We investigate which factors are predictive of whether transitive verb phrases are passivized. We show the increasing importance of the person-hierarchy effects observed by Bresnan et al. (2001), with increasing strength of the constraint against passivizing clauses with local agents, as well as the rising prevalence of such agents. Moreover, our ablation experiments on the Wall Street Journal and Hansard corpora provide support for the unmarked information structure of ‘given’ before ‘new’ noted by Halliday (1967).


A Hierarchical Model For Heterogenous Reliability Field Data, Eric Thomas Mittman, Colin Lewis-Beck, William Q. Meeker 2018 Iowa State University

A Hierarchical Model For Heterogenous Reliability Field Data, Eric Thomas Mittman, Colin Lewis-Beck, William Q. Meeker

Statistics Publications

When analyzing field data on consumer products, model-based approaches to inference require a model with sufficient flexibility to account for multiple kinds of failure. The causes of failure, while not interesting to the consumer per se, can lead to various observed lifetime distributions. Because of this, standard lifetime models, such as Weibull or lognormal may be inadequate. Usually cause-of-failure information will not be available to the consumer and thus traditional competing risk analyses cannot be performed. Furthermore, when the information carried by lifetime data are limited by sample size, censoring and truncation, estimates can be unstable and suffer from imprecision ...


Big Data And Parkinson’S Disease: Exploration, Analyses, And Data Challenges, Mahalakshmi SenthilarumugamVeilukandammal, Sree Nilakanta, Baskar Ganapathysubramanian, Vellareddy Anantharam, Anumantha Kanthasamy, Auriel A. Willette 2018 Iowa State University

Big Data And Parkinson’S Disease: Exploration, Analyses, And Data Challenges, Mahalakshmi Senthilarumugamveilukandammal, Sree Nilakanta, Baskar Ganapathysubramanian, Vellareddy Anantharam, Anumantha Kanthasamy, Auriel A. Willette

Mechanical Engineering Conference Presentations, Papers, and Proceedings

In healthcare, a tremendous amount of clinical and laboratory tests, imaging, prescription and medication data are being collected. Big data analytics on these data aim at early detection of disease which will help in developing preventive measures and in improving patient care. Parkinson disease is the second-most common neurodegenerative disorder in the United States. To find a cure for Parkinson's disease biological, clinical and behavioral data of different cohorts are collected, managed and propagated through Parkinson’s Progression Markers Initiative (PPMI). Applying big data technology to this data will lead to the identification of the potential biomarkers of Parkinson ...


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