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Creating A Better Technological Piano Practice Aid With Knowledge Tracing, Max Feldkamp 2018 University of Colorado, Boulder

Creating A Better Technological Piano Practice Aid With Knowledge Tracing, Max Feldkamp

Keyboard Graduate Theses & Dissertations

Modern music tutoring software and mobile instructional applications have great potential to help students practice at home effectively. They can offer extensive feedback on what the student is getting right and wrong and have adopted a gamified design with levels, badges, and other game-like elements to help gain wider appeal among students. Despite their advantages for motivating students and creating a safe practice environment, no current music instruction software demonstrates any knowledge about a student’s level of mastery. This can lead to awkward pedagogy and user frustration. Applying Bayesian Knowledge Tracing to tutoring systems provides an ideal way to ...


A Comparison Of R, Sas, And Python Implementations Of Random Forests, Breckell Soifua 2018 Utah State University

A Comparison Of R, Sas, And Python Implementations Of Random Forests, Breckell Soifua

All Graduate Plan B and other Reports

The Random Forest method is a useful machine learning tool developed by Leo Breiman. There are many existing implementations across different programming languages; the most popular of which exist in R, SAS, and Python. In this paper, we conduct a comprehensive comparison of these implementations with regards to the accuracy, variable importance measurements, and timing. This comparison was done on a variety of real and simulated data with different classification difficulty levels, number of predictors, and sample sizes. The comparison shows unexpectedly different results between the three implementations.


Implementing The Use Of Personal Activity Data In An Introductory Statistics Course, Lacy Christensen 2018 Utah State University

Implementing The Use Of Personal Activity Data In An Introductory Statistics Course, Lacy Christensen

All Graduate Theses and Dissertations

Integrating real data into a classroom is one of the recommendations in the Guidelines for Assessment and Instruction in Statistics Education (GAISE) college report which lays out guidelines for an introductory statistics course (Committee, GAISE College Report ASA Revision, 2016). In order to assess the effect of using real data in a classroom, the students received physical activity trackers to wear during an undergraduate introductory statistics course taught in the summer. This tracker, a Fitbit, enabled students to monitor and record their steps, calories, and active time throughout the class. Collecting personal activity data (PAD) creates a large database which ...


Computer Aided Clinical Trials For Implantable Cardiac Devices, Rahul Mangharam 2018 University of Pennsylvania

Computer Aided Clinical Trials For Implantable Cardiac Devices, Rahul Mangharam

Real-Time and Embedded Systems Lab (mLAB)

In this paper we aim to answer the question, ``How can modeling and simulation of physiological systems be used to evaluate life-critical implantable medical devices?'' Clinical trials for medical devices are becoming increasingly inefficient as they take several years to conduct, at very high cost and suffer from high rates of failure. For example, the Rhythm ID Goes Head-to-head Trial (RIGHT) sought to evaluate the performance of two arrhythmia discriminator algorithms for implantable cardioverter defibrillators, Vitality 2 vs. Medtronic, in terms of time-to-first inappropriate therapy, but concluded with results contrary to the initial hypothesis - after 5 years, 2,000+ patients ...


A Bayesian Beta-Mixture Model For Nonparametric Irt (Bbm-Irt), Ethan A. Arenson, George Karabatsos 2018 University of Illinois at Chicago

A Bayesian Beta-Mixture Model For Nonparametric Irt (Bbm-Irt), Ethan A. Arenson, George Karabatsos

Journal of Modern Applied Statistical Methods

Item response models typically assume that the item characteristic (step) curves follow a logistic or normal cumulative distribution function, which are strictly monotone functions of person test ability. Such assumptions can be overly-restrictive for real item response data. A simple and more flexible Bayesian nonparametric IRT model for dichotomous items is introduced, which constructs monotone item characteristic (step) curves by a finite mixture of beta distributions, which can support the entire space of monotone curves to any desired degree of accuracy. An adaptive random-walk Metropolis-Hastings algorithm is proposed to estimate the posterior distribution of the model parameters. The Bayesian IRT ...


Calculus Of The Impossible: Review Of The Improbability Principle (2014) By David Hand And The Logic Of Miracles (2018) By Lásló Mérő, Samuel L. Tunstall 2018 Michigan State University

Calculus Of The Impossible: Review Of The Improbability Principle (2014) By David Hand And The Logic Of Miracles (2018) By Lásló Mérő, Samuel L. Tunstall

Numeracy

David J. Hand. 2014. The Improbability Principle: Why Coincidences, Miracles, and Rare Events Happen Every Day (New York, NY: Scientific American/Farrar, Straus and Giroux) 288 pp. ISBN: 978-0374175344.

Lásló Mérő. 2018. The Logic of Miracles: Making Sense of Rare, Really Rare, and Impossibly Rare Events (New Haven, CT: Yale University Press) 288 pp. ISBN: 978-0300224153.

David Hand and Lásló Mérő both grapple with the occurrence of seemingly impossible events in these two popular science books. In this comparative review, I describe the two books, and explain why I prefer Hand's treatment of the impossible.


Robust Estimation And Inference On Current Status Data With Applications To Phase Iv Cancer Trial, Deo Kumar Srivastava, Liang Zhu, Melissa M. Hudson, Jianmin Pan, Shesh N. Rai 2018 St. Jude Children's Research Hospital

Robust Estimation And Inference On Current Status Data With Applications To Phase Iv Cancer Trial, Deo Kumar Srivastava, Liang Zhu, Melissa M. Hudson, Jianmin Pan, Shesh N. Rai

Journal of Modern Applied Statistical Methods

The use of piecewise exponential distributions was proposed by Rai et al. (2013) for analyzing cardiotoxicity data. Some parametric models are proposed, but the focus is on the Weibull distribution, which overcomes the limitation of piecewise exponential.


Mathematical Models, Patty Wagner, Marnie Phipps 2018 University of North Georgia

Mathematical Models, Patty Wagner, Marnie Phipps

Mathematics Grants Collections

This Grants Collection for Mathematical Models was created under a Round Nine 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


Analysis Of Belonging And Retention: Fall 2017 Nef, Karteek Reddy Tummala 2018 St. Cloud State University

Analysis Of Belonging And Retention: Fall 2017 Nef, Karteek Reddy Tummala

SCSU Data

The analysis on enrollment of students is important to any university in planning the academics, course curriculum and many other things to ensure the students get best campus experience. The main goal of this analysis is to determine the reason for low retention rate based on the Social Belonging Index(SBI) and Academic Belonging Index(ABI) and demonstrate the accuracy of analysis on previous retention results to further strengthen the analysis.


Ace Students' Performance, Abdoul Kader Naze 2018 St. Cloud State University

Ace Students' Performance, Abdoul Kader Naze

SCSU Data

ACE stands for Academic Collegiate Excellence and is a program for students who did not meet at first the St Cloud State University admission criteria. Being admitted to St Cloud State through the program will allow students to have access to academic and social support through their transition into university life. This program also has for goal to mold those students through a successful academic path.

The admission into ACE can be done either by Auto-Admission or by Referral to the program. In fact, students who are ACE Auto-Admits are required to have at least an ACT score of 21 ...


Robust Heteroscedasticity Consistent Covariance Matrix Estimator Based On Robust Mahalanobis Distance And Diagnostic Robust Generalized Potential Weighting Methods In Linear Regression, M. Habshah, Muhammad Sani, Jayanthi Arasan 2018 Universiti Putra Malaysia

Robust Heteroscedasticity Consistent Covariance Matrix Estimator Based On Robust Mahalanobis Distance And Diagnostic Robust Generalized Potential Weighting Methods In Linear Regression, M. Habshah, Muhammad Sani, Jayanthi Arasan

Journal of Modern Applied Statistical Methods

The violation of the assumption of homoscedasticity and the presence of high leverage points (HLPs) are common in the use of regression models. The weighted least squares can provide the solution to heteroscedastic regression model if the heteroscedastic error structures are known. Based on Furno (1996), two robust weighting methods are proposed based on HLP detection measures (robust Mahalanobis distance based on minimum volume ellipsoid and diagnostic robust generalized potential based on index set equality (DRGP(ISE)) on robust heteroscedasticity consistent covariance matrix estimators. Results obtained from a simulation study and real data sets indicated the DRGP(ISE) method is ...


The Study Design Elements Employed By Researchers In Preclinical Animal Experiments From Two Research Domains And Implications For Automation Of Systematic Reviews, Annette M. O'Connor, Sarah C. Totton, Jonah C. Cullen, Mahmood Ramezani, Vijay Kalivarapu, Chaohui Yuan, Stephen B. Gilbert 2018 Iowa State University

The Study Design Elements Employed By Researchers In Preclinical Animal Experiments From Two Research Domains And Implications For Automation Of Systematic Reviews, Annette M. O'Connor, Sarah C. Totton, Jonah C. Cullen, Mahmood Ramezani, Vijay Kalivarapu, Chaohui Yuan, Stephen B. Gilbert

Veterinary Diagnostic and Production Animal Medicine Publications

Systematic reviews are increasingly using data from preclinical animal experiments in evidence networks. Further, there are ever-increasing efforts to automate aspects of the systematic review process. When assessing systematic bias and unit-of-analysis errors in preclinical experiments, it is critical to understand the study design elements employed by investigators. Such information can also inform prioritization of automation efforts that allow the identification of the most common issues. The aim of this study was to identify the design elements used by investigators in preclinical research in order to inform unique aspects of assessment of bias and error in preclinical research. Using 100 ...


Internal Consistency Reliability In Measurement: Aggregate And Multilevel Approaches, Georgios Sideridis, Abdullah Saddaawi, Khaleel Al-Harbi 2018 Harvard Medical School

Internal Consistency Reliability In Measurement: Aggregate And Multilevel Approaches, Georgios Sideridis, Abdullah Saddaawi, Khaleel Al-Harbi

Journal of Modern Applied Statistical Methods

The purpose of the present paper was to evaluate the internal consistency reliability of the General Teacher Test assuming clustered and non-clustered data using commercial software (Mplus). Participants were 2,000 testees who were selected using random sampling from a larger pool of examinees (more than 65k). The measure involved four factors, namely: (a) planning for learning, (b) promoting learning, (c) supporting learning, and (d) professional responsibilities and was hypothesized to comprise a unidimensional instrument assessing generalized skills and competencies. Intra-class correlation coefficients and variance ratio statistics suggested the need to incorporate a clustering variable (i.e., university) when evaluating ...


Fitting The Rasch Model Under The Logistic Regression Framework To Reduce Estimation Bias, Tianshu Pan 2018 Pearson

Fitting The Rasch Model Under The Logistic Regression Framework To Reduce Estimation Bias, Tianshu Pan

Journal of Modern Applied Statistical Methods

This article showed how and why the Rasch model can be fitted under the logistic regression framework. Then a penalized maximum likelihood (Firth 1993) for logistic regression models can also be used to reduce ML biases when fitting the Rasch model. These conclusions are supported by a simulation study.


Regressions Regularized By Correlations, Stan Lipovetsky 2018 GfK North America

Regressions Regularized By Correlations, Stan Lipovetsky

Journal of Modern Applied Statistical Methods

The regularization of multiple regression by proportionality to correlations of predictors with dependent variable is applied to the least squares objective and normal equations to relax the exact equalities and to get a robust solution. This technique produces models not prone to multicollinearity and is very useful in practical applications.


Optimum Stratification In Bivariate Auxiliary Variables Under Neyman Allocation, Faizan Danish, S.E.H. Rizvi 2018 Sher-e-Kashmir University of Agricultural Sciences and Technology of Jammu, J&K India

Optimum Stratification In Bivariate Auxiliary Variables Under Neyman Allocation, Faizan Danish, S.E.H. Rizvi

Journal of Modern Applied Statistical Methods

In several situations complete data set of the study variable is unknown that becomes a stumbling block in various stratification techniques in order to obtain stratification points on two way stratification method. In this paper a technique has been proposed under Neyman allocation when the stratification is done oj the two auxiliary variable having one estimation variable under consideration. Due to complexities created by minimal equations approximate optimum strata boundaries has been obtained. Empirical study has been done to illustrate the proposed method when the auxiliary variables have standard Cauchy and power distributions.


An Explanatory Study On The Non-Parametric Multivariate T2 Control Chart, Abdolrasoul Mostajeran, Nasrolah Iranpanah, Rassoul Noorossana 2018 Department of Statistics, University of Isfahan, Isfahan, Iran

An Explanatory Study On The Non-Parametric Multivariate T2 Control Chart, Abdolrasoul Mostajeran, Nasrolah Iranpanah, Rassoul Noorossana

Journal of Modern Applied Statistical Methods

Most control charts require the assumption of normal distribution for observations. When distribution is not normal, one can use non-parametric control charts such as sign control chart. A deficiency of such control charts could be the loss of information due to replacing an observation with its sign or rank. Furthermore, because the chart statistics of T2 are correlated, the T2 chart is not a desire performance. Non-parametric bootstrap algorithm could help to calculate control chart parameters using the original observations while no assumption regarding the distribution is needed. In this paper, first, a bootstrap multivariate control chart is ...


Statistical Biophysics Blog: Recovering From Bootstrap Intoxication, Daniel M. Zuckerman 2018 Oregon Health & Science University

Statistical Biophysics Blog: Recovering From Bootstrap Intoxication, Daniel M. Zuckerman

Scholar Archive

When analyzing statistical uncertainty for large-variance data sets with small sample sizes, the 'bootstrap' method must viewed with great caution.


A Comparison Of The Predictive Ability Of Logistic Regression And Time Series Analysis On Business Credit Data, Lauren Staples 2018 Kennesaw State University

A Comparison Of The Predictive Ability Of Logistic Regression And Time Series Analysis On Business Credit Data, Lauren Staples

Grey Literature from PhD Candidates

The credit industry creates models to determine the risk of lending money to consumers as well as to commercial customers. These models are heavily regulated in the U.S. as well as in other countries. Model inputs must be explainable to customers as well as to regulators. Two such modeling approaches that are currently commonly used are logistic regression models and time series models. This paper steps through the preprocessing and model building of these two models on a large commercial data set and compares the predictive ability of these two methods. The two models achieved similar accuracy results: the ...


Combining Academics And Social Engagement: A Major-Specific Early Alert Method To Counter Student Attrition In Science, Technology, Engineering, And Mathematics, Andrew J. Sage, Cinzia Cervato, Ulrike Genschel, Craig Ogilvie 2018 Iowa State University

Combining Academics And Social Engagement: A Major-Specific Early Alert Method To Counter Student Attrition In Science, Technology, Engineering, And Mathematics, Andrew J. Sage, Cinzia Cervato, Ulrike Genschel, Craig Ogilvie

Geological and Atmospheric Sciences Publications

Students are most likely to leave science, technology, engineering, and mathematics (STEM) majors during their first year of college. We developed an analytic approach using random forests to identify at-risk students. This method is deployable midway through the first semester and accounts for academic preparation, early engagement in university life, and performance on midterm exams. By accounting for cognitive and noncognitive factors, our method achieves stronger predictive performance than would be possible using cognitive or noncognitive factors alone. We show that it is more difficult to predict whether students will leave STEM than whether they will leave the institution. More ...


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