Open Access. Powered by Scholars. Published by Universities.®

Physical Sciences and Mathematics Commons

Open Access. Powered by Scholars. Published by Universities.®

Statistics

Selected Works

Discipline
Institution
Publication Year
Publication
File Type

Articles 1 - 30 of 41

Full-Text Articles in Physical Sciences and Mathematics

A Bayesian Approach To Deriving Ages Of Individual Field White Dwarfs, Erin M. O'Malley, Ted Von Hippel, David A. Van Dyk Aug 2019

A Bayesian Approach To Deriving Ages Of Individual Field White Dwarfs, Erin M. O'Malley, Ted Von Hippel, David A. Van Dyk

Ted von Hippel

We apply a self-consistent and robust Bayesian statistical approach to determine the ages, distances, and zero-age main sequence (ZAMS) masses of 28 field DA white dwarfs (WDs) with ages of approximately 4-8 Gyr. Our technique requires only quality optical and near-infrared photometry to derive ages with <15% uncertainties, generally with little sensitivity to our choice of modern initial-final mass relation. We find that age, distance, and ZAMS mass are correlated in a manner that is too complex to be captured by traditional error propagation techniques. We further find that the posterior distributions of age are often asymmetric, indicating that the standard approach to deriving WD ages can yield misleading results.


Differentially Expressed Genes In Blood From Young Pigs Between Two Swine Lines Divergently Selected For Feed Efficiency: Potential Biomarkers For Improving Feed Efficiency, Haibo Liu, Yet T. Nguyen, Daniel S. Nettleton, Jack C. M. Dekkers, Christopher K. Tuggle Jun 2019

Differentially Expressed Genes In Blood From Young Pigs Between Two Swine Lines Divergently Selected For Feed Efficiency: Potential Biomarkers For Improving Feed Efficiency, Haibo Liu, Yet T. Nguyen, Daniel S. Nettleton, Jack C. M. Dekkers, Christopher K. Tuggle

Dan Nettleton

The goal of this study was to find potential gene expression biomarkers in blood of piglets that can be used to predict pigs’ future feed efficiency. Using RNA-seq technology, we found 453 genes were differentially expressed (false discovery rate (FDR) ≤ 0.05) in the blood of two Yorkshire lines of pigs divergently selected for feed efficiency (FE) based on residual feed intake (RFI). Genes involved in several biosynthetic processes were overrepresented among genes more highly expressed in the low RFI line compared to the high RFI line. Weighted gene co-expression network analysis (WGCNA) also revealed genes involved in some of …


A Self-Contained Course In The Mathematical Theory Of Statistics For Scientists & Engineers With An Emphasis On Predictive Regression Modeling & Financial Applications., Tim Smith Apr 2019

A Self-Contained Course In The Mathematical Theory Of Statistics For Scientists & Engineers With An Emphasis On Predictive Regression Modeling & Financial Applications., Tim Smith

Timothy Smith

Preface & Acknowledgments

This textbook is designed for a higher level undergraduate, perhaps even first year graduate, course for engineering or science students who are interested to gain knowledge of using data analysis to make predictive models. While there is no statistical perquisite knowledge required to read this book, due to the fact that the study is designed for the reader to truly understand the underlying theory rather than just learn how to read computer output, it would be best read with some familiarity of elementary statistics. The book is self-contained and the only true perquisite knowledge is a solid …


The Gaise College Report: The American Statistical Association Meets Sound Pedagogy In Central Virginia, Beverly Wood Nov 2018

The Gaise College Report: The American Statistical Association Meets Sound Pedagogy In Central Virginia, Beverly Wood

Beverly Wood

Research in undergraduate statistics education often centers on the introductory course required for a large percentage of college students. While acknowledging the diverse setting, audience, and purpose of introductory courses, existing research assumes that courses offered by different disciplines share the same goals and teaching practices. The purpose of this study is to examine the objectives for student outcomes and pedagogical delivery of introductory statistics courses in various academic departments to provide explicit evidence for this assumption. The American Statistical Association’s Guidelines for Assessment and Instruction in Statistics Education (GAISE) are meant to apply to all introductory courses. The College …


Guidelines For Assessment And Instruction In Statistics Education (Gaise) College Report 2016, Robert Carver, Michelle Everson, John Gabrosek, Nicholas Horton, Robin Lock, Megan Mocko, Allan Rossman, Ginger Holmes Roswell, Paul Velleman, Jeffrey Witmer, Beverly Wood Nov 2018

Guidelines For Assessment And Instruction In Statistics Education (Gaise) College Report 2016, Robert Carver, Michelle Everson, John Gabrosek, Nicholas Horton, Robin Lock, Megan Mocko, Allan Rossman, Ginger Holmes Roswell, Paul Velleman, Jeffrey Witmer, Beverly Wood

Beverly Wood

In 2005 the American Statistical Association (ASA) endorsed the Guidelines for Assessment and Instruction in Statistics Education (GAISE) College Report. This report has had a profound impact on the teaching of introductory statistics in two- and four-year institutions, and the six recommendations put forward in the report have stood the test of time. Much has happened within the statistics education community and beyond in the intervening 10 years, making it critical to re-evaluate and update this important report. For readers who are unfamiliar with the original GAISE College Report or who are new to the statistics education community, the full …


Data Analysis Basics – Part Ii, Judith A. Savageau Mar 2018

Data Analysis Basics – Part Ii, Judith A. Savageau

Judith A. Savageau

Blog post to AEA365, a blog sponsored by the American Evaluation Association (AEA) dedicated to highlighting Hot Tips, Cool Tricks, Rad Resources, and Lessons Learned for evaluators. The American Evaluation Association is an international professional association of evaluators devoted to the application and exploration of program evaluation, personnel evaluation, technology, and many other forms of evaluation. Evaluation involves assessing the strengths and weaknesses of programs, policies, personnel, products, and organizations to improve their effectiveness.


Data Analysis Basics – Part I, Judith A. Savageau Mar 2018

Data Analysis Basics – Part I, Judith A. Savageau

Judith A. Savageau

Blog post to AEA365, a blog sponsored by the American Evaluation Association (AEA) dedicated to highlighting Hot Tips, Cool Tricks, Rad Resources, and Lessons Learned for evaluators. The American Evaluation Association is an international professional association of evaluators devoted to the application and exploration of program evaluation, personnel evaluation, technology, and many other forms of evaluation. Evaluation involves assessing the strengths and weaknesses of programs, policies, personnel, products, and organizations to improve their effectiveness.


Teaching Statistics To Msw Students: Comparing Credit And Non-Credit Options, Ashley Davis, Rebecca G. Mirick Dec 2017

Teaching Statistics To Msw Students: Comparing Credit And Non-Credit Options, Ashley Davis, Rebecca G. Mirick

Rebecca Mirick

In professional disciplines like social work, students are expected to be able to understand and apply basic statistical concepts. Graduate programs differ in how they expect students to develop this ability; some require a full-credit statistics course as a prerequisite to admission, and others incorporate statistics into social work research courses. The for-credit requirement has a high financial and time cost for students. This exploratory study examined the feasibility of replacing this requirement with a brief, non-credit statistics course. MSW students (n=168) who took both types of courses were surveyed. No association was found between the type of course and …


Luna Gsa Fall 2017 Poster.Pptx, Melissa Luna Oct 2017

Luna Gsa Fall 2017 Poster.Pptx, Melissa Luna

Melissa Luna


The Antarctic is important to study to further our understanding of global climate regulation. One of the objectives in Antarctic research is to understand how, where, and why ice sheets lose mass, a critical component of climate change. The Antarctic ice sheet consists of about 26.5 million cubic kilometers of ice, enough to raise global sea levels by an average of 60 meters (Kennicutt, 2014). Although the ice sheets were stable for the last several thousand years, the Antarctic ice sheet is now losing ice at an accelerating pace due to global climate change, attributed to increased atmospheric CO2 levels. …


Statistical Contributions To Bioinformatics: Design, Modeling, Structure Learning, And Integration, Jeffrey S. Morris, Veera Baladandayuthapani Dec 2016

Statistical Contributions To Bioinformatics: Design, Modeling, Structure Learning, And Integration, Jeffrey S. Morris, Veera Baladandayuthapani

Jeffrey S. Morris

The advent of high-throughput multi-platform genomics technologies providing whole-genome molecular summaries of biological samples has revolutionalized biomedical research. These technologies yield highly structured big data, whose analysis poses significant quantitative challenges. The field of Bioinformatics has emerged to deal with these challenges, and is comprised of many quantitative and biological scientists working together to eectively process these data and extract the treasure trove of information they contain. Statisticians, with their deep understanding of variability and uncertainty quantification, play a key role in these efforts. In this article, we attempt to summarize some of the key contributions of statisticians to bioinformatics, …


Corn-Soybean And Alternative Cropping Systems Effects On No 3 -N Leaching Losses In Subsurface Drainage Water, Rameshwar S. Kanwar, Richard M. Cruse, Mohammadreza Ghaffarzadeh, Allah Bakhsh, Douglas Karlen, Theodore B. Bailey Dec 2015

Corn-Soybean And Alternative Cropping Systems Effects On No 3 -N Leaching Losses In Subsurface Drainage Water, Rameshwar S. Kanwar, Richard M. Cruse, Mohammadreza Ghaffarzadeh, Allah Bakhsh, Douglas Karlen, Theodore B. Bailey

Douglas L Karlen

Alternative cropping systems can improve resource use efficiency, increase corn grain yield, and help in reducing negative impacts on the environment. A 6-yr (1993 to 1998) field study was conducted at the Iowa State University’s Northeastern Research Center near Nashua, Iowa, to evaluate the effects of non-traditional cropping systems [strip inter cropping (STR)-corn (Zea mays L.)/soybean (Glycine max L.)/oats (Avina sativa L.)]; alfalfa rotation (ROT)-3-yr (1993 to 1995) alfalfa (Medicago sativa L.) followed by corn in 1996, soybean in 1997, and oats in 1998), and traditional cropping system (corn after soybean (CS) and soybean after corn (SC) on the flow …


Cropping System Effects On No3-N Loss With Subsurface Drainage Water, Allah Bakhsh, Rameshwar S. Kanwar, Theodore B. Bailey, Cynthia A. Cambardella, Douglas Karlen, Thomas S. Colvin Dec 2015

Cropping System Effects On No3-N Loss With Subsurface Drainage Water, Allah Bakhsh, Rameshwar S. Kanwar, Theodore B. Bailey, Cynthia A. Cambardella, Douglas Karlen, Thomas S. Colvin

Douglas L Karlen

An appropriate combination of tillage and nitrogen management practices will be necessary to develop sustainable farming practices. A six–year (1993–1998) field study was conducted on subsurface–drained Clyde–Kenyon–Floyd soils to quantify the impact of two tillage systems (chisel plow vs. no tillage) and two N fertilizer management practices (preplant single application vs. late–spring soil test based application) on nitrate–nitrogen (NO3–N) leaching loss with subsurface drain discharge from corn (Zea mays L.) soybean (Glycine max L.) rotation plots. Preplant injected urea ammonium nitrate solution (UAN) fertilizer was applied at the rate of 110 kg ha–1 to chisel plow and no–till corn plots, …


Measuring Gender Difference In Information Sharing Using Network Analysis: The Case Of The Austrian Interlocking Directorship Network In 2009, Carlo Drago, Livia Amidani Aliberti, Davide Carbonai Jul 2014

Measuring Gender Difference In Information Sharing Using Network Analysis: The Case Of The Austrian Interlocking Directorship Network In 2009, Carlo Drago, Livia Amidani Aliberti, Davide Carbonai

Carlo Drago

In recent literature a relevant problem has been the relationship between career/personal contact networks and different career paths. In addition the recent advances in social capital theory have shown the way in which networks impact on personal careers. In particular women’s careers appear to be negatively affected by the informational network structure. The main contribution of this work is to propose empirical evidence of this phenomenon by considering the gendered directorship network with relation to Austria and to show the structural differences by gender in the network. By using community detection techniques we have found various communities in which females …


Reference Interval Studies: What Is The Maximum Number Of Samples Recommended?, Robert Hawkins, Tony Badrick Sep 2013

Reference Interval Studies: What Is The Maximum Number Of Samples Recommended?, Robert Hawkins, Tony Badrick

Tony Badrick

Background: Little attention has been paid to the maximum number of specimens for reference interval calculation, i.e., the number of specimens beyond which there is no further benefit in reference interval calculation. We present a model for the estimation of the maximum number of specimens for reference interval studies based on setting the 90% confidence interval of the reference limits to be equal to the analyte reporting interval. Methods: Equations describing the bounds on the upper and lower 90% confidence intervals for logarithmically transformed and untransformed data were derived and applied to determine the maximum number of specimens required to …


Spatial Statistics In The Presence Of Location Error With An Application To Remote Sensing Of The Environment, Noel A. Cressie, John Kornak Feb 2013

Spatial Statistics In The Presence Of Location Error With An Application To Remote Sensing Of The Environment, Noel A. Cressie, John Kornak

Professor Noel Cressie

Techniques for the analysis of spatial data have, to date, tended to ignore any effect caused by error in specifying the spatial locations at which measurements are recorded. This paper reviews the methods for adjusting spatial inference in the presence of data-location error, particularly for data that. have a continuous spatial index (geostatistical data). New kriging equations are developed and evaluated based on a simulation experiment. They are also applied to remote-sensing data from the Total Ozone Mapping Spectrometer instrument on the Nimbus-7 satellite, where the location error is caused by assignment of the data to their nearest grid-cell centers. …


Size And Power Considerations For Testing Loglinear Models Using Divergence Test Statistics, Noel A. Cressie, L Pardo, M Del Carmen Pardo Feb 2013

Size And Power Considerations For Testing Loglinear Models Using Divergence Test Statistics, Noel A. Cressie, L Pardo, M Del Carmen Pardo

Professor Noel Cressie

In this article, we assume that categorical data are distributed according to a multinomial distribution whose probabilities follow a loglinear model. The inference problem we consider is that of hypothesis testing in a loglinear-model setting. The null hypothesis is a composite hypothesis nested within the alternative. Test statistics are chosen from the general class of divergence statistics. This article collects together the operating characteristics of the hypothesis test based on both asymptotic (using large-sample theory) and finite-sample (using a designed simulation study) results. Members of the class of power divergence statistics are compared, and it is found that the Cressie-Read …


Data Mining Of Misr Aerosol Product Using Spatial Statistics, Tao Shi, Noel A. Cressie Feb 2013

Data Mining Of Misr Aerosol Product Using Spatial Statistics, Tao Shi, Noel A. Cressie

Professor Noel Cressie

In climate models, aerosol forcing is the major source of uncertainty in climate forcing, over the industrial period. To reduce this uncertainty, instruments on satellites have been put in place to collect global data. However, missing and noisy observations impose considerable difficulties for scientists researching global aerosol distribution, aerosol transportation, and comparisons between satellite observations and global-climate-model outputs. In this paper, we propose a Spatial Mixed Effects (SME) statistical model to predict the missing values, denoise the observed values, and quantify the spatial-prediction uncertainties. The computations associated with the SME model are linear scalable to the number of data points, …


Estimation Of Hiv Incidence Using Multiple Biomakers, Ron Brookmeyer, Jacob Konikoff, Oliver Laeyendecker, Susan Eshleman Jan 2013

Estimation Of Hiv Incidence Using Multiple Biomakers, Ron Brookmeyer, Jacob Konikoff, Oliver Laeyendecker, Susan Eshleman

Ron Brookmeyer

The incidence of human immunodeficiency virus (HIV) is the rate at which new HIV infections occur in populations. The development of accurate, practical, and cost-effective approaches to estimation of HIV incidence is a priority among researchers in HIV surveillance because of limitations with existing methods. In this paper, we develop methods for estimating HIV incidence rates using multiple biomarkers in biological samples collected from a cross-sectional survey. An advantage of the method is that it does not require longitudinal follow-up of individuals. We use assays for BED, avidity, viral load, and CD4 cell count data from clade B samples collected …


Decomposition Of High Frequency Data In Components: Visualization And Interpretative Models, Carlo Drago May 2012

Decomposition Of High Frequency Data In Components: Visualization And Interpretative Models, Carlo Drago

Carlo Drago

No abstract provided.


A Note On The Indeterminacy And Arbitrariness Of Pena’S Method Of Construction Of Synthetic Indicators, Sudhanshu K. Mishra Mar 2012

A Note On The Indeterminacy And Arbitrariness Of Pena’S Method Of Construction Of Synthetic Indicators, Sudhanshu K. Mishra

Sudhanshu K Mishra

In this paper we demonstrate that Pena’s method of construction of a synthetic indicator is very sensitive to the order in which the constituent variables (whose linear aggregation yields the synthetic indicator) are arranged. Since m number of constituent variables may be arranged in m-factorial ways, even a moderately large m can give rise to a very large number of synthetic indicators from which one cannot choose the one which best represents the constituent variables. Given that an analyst has too little information as to the order in which a sizeable number of constituent variables must be arranged so as …


Application Of A Data Mining Framework For The Identification Of Agricultural Production Areas In Wa , Yunous Vagh, Leisa Armstrong, Dean Diepeveen Feb 2012

Application Of A Data Mining Framework For The Identification Of Agricultural Production Areas In Wa , Yunous Vagh, Leisa Armstrong, Dean Diepeveen

Leisa Armstrong

This paper will propose a data mining framework for the identification of agricultural production areas ill WA. The data mining (DM) framework was developed with the aim of enhancing the analysis of agricultural datasets compared to currently used statistical methods. The DM framework is a synthesis of different technologies brought together for the purpose of enhancing the interrogation of these datasets. The DM framework is based on the data, information, knowledge and wisdom continuum as a horizontal axis, with DM and online analytical processing (OLAP) forming the vertical axis. In addition the DM framework incorporates aspects of data warehousing phases, …


The Dirty “S” Word: Innovative Teaching Techniques For Counselor Educators Facilitating Learning In Statistics And Research, Rebecca L. Tadlock-Marlo, Megan Michalak Jan 2012

The Dirty “S” Word: Innovative Teaching Techniques For Counselor Educators Facilitating Learning In Statistics And Research, Rebecca L. Tadlock-Marlo, Megan Michalak

Rebecca L Tadlock-Marlo

Innovative pedagogy will be presented and discussed to help make research a less painful class to both teach and learn. Foci include teaching methods, potential assignments, and suggestions for activities to help facilitate a more fluid learning process for counselors. Attendees will explore aspects of helping students overcome their fear of both statistics and research.


Beyond Multiple Regression: Using Commonality Analysis To Better Understand R2 Results, Russell Warne Sep 2011

Beyond Multiple Regression: Using Commonality Analysis To Better Understand R2 Results, Russell Warne

Russell T Warne

Multiple regression is one of the most common statistical methods used in quantitative educational research. Despite the versatility and easy interpretability of multiple regression, it has some shortcomings in the detection of suppressor variables and for somewhat arbitrarily assigning values to the structure coefficients of correlated independent variables. Commonality analysis—heretofore rarely used in gifted education research—is a statistical method that partitions the explained variance of a dependent variable into nonoverlapping parts according to the independent variable(s) that are related to each portion. This Methodological Brief includes an example of commonality analysis and equations for researchers who wish to conduct their …


A Statistical Test For The Capacity Coefficient, Joseph W. Houpt, James T. Townsend Jul 2011

A Statistical Test For The Capacity Coefficient, Joseph W. Houpt, James T. Townsend

Joseph W. Houpt

No abstract provided.


Statistics In Law: Bad Inferences & Uncommon Sense, Curtis E.A. Karnow Jan 2011

Statistics In Law: Bad Inferences & Uncommon Sense, Curtis E.A. Karnow

Curtis E.A. Karnow

A review of classic fallacies in statistics and probability in the courts. The article briefly, and in plain English, provides an introduction to probability theory, and randomness.


National Estimates Of The Prevalence Of Alzheimer's Disease In The United States, Ron Brookmeyer, Denis Evans, Liesi Hebert, Langa Kenneth, Heeringa Steven, Plassman Brenda, Kukull Kenneth Dec 2010

National Estimates Of The Prevalence Of Alzheimer's Disease In The United States, Ron Brookmeyer, Denis Evans, Liesi Hebert, Langa Kenneth, Heeringa Steven, Plassman Brenda, Kukull Kenneth

Ron Brookmeyer

Several methods of estimating prevalence of dementia are presented in this article. For both Brookmeyer and the Chicago Health and Aging project (CHAP), the estimates of prevalence are derived statistically, forward calculating from incidence and survival figures. The choice of incidence rates on which to build the estimates may be critical. Brookmeyer used incidence rates from several published studies, whereas the CHAP investigators applied the incidence rates observed in their own cohort. The Aging, Demographics, and Memory Study (ADAMS) and the East Boston Senior Health Project (EBSHP) were sample surveys designed to ascertain the prevalence of Alzheimer’s disease and dementia. …


Big Macs And Eigenfactor Scores: Don't Let The Correlation Coefficients Fool You, Jevin D. West, Carl T. Bergstrom, Theodore C. Bergstrom Apr 2010

Big Macs And Eigenfactor Scores: Don't Let The Correlation Coefficients Fool You, Jevin D. West, Carl T. Bergstrom, Theodore C. Bergstrom

Ted C Bergstrom

A recent article by Phil Davis suggested that the Eigenvalue metric does adds little useful information to the more simply calculated measure of total citations published by the ISI. This paper argues that Davis's claim is an instance of a classic statistical fallacy of spurious correlation. Based on an analysis of the entire 2006 ISI Journal Citation Reports, we show that there are statistically and economically significant differences between the Eigenfactor metrics and the ISI's impact factor and total citations.


Temporal Changes In The Parameters Of Statistical Distribution Of Journal Impact Factor, Sudhanshu K. Mishra Mar 2010

Temporal Changes In The Parameters Of Statistical Distribution Of Journal Impact Factor, Sudhanshu K. Mishra

Sudhanshu K Mishra

Statistical distribution of Journal Impact Factor (JIF) is characteristically asymmetric and non-mesokurtic. Even the distribution of log10(JIF) exhibits conspicuous skewness and non-mesokurticity. In this paper we estimate the parameters of Johnson SU distribution fitting to the log10(JIF) data for 10 years, 1999 through 2008, and study the temporal variations in those estimated parameters. We also study ‘over-the-samples stability’ in the estimated parameters for each year by the method of re-sampling close to bootstrapping. It has been found that log10(JIF) is Pearson-IV distributed. Johnson SU distribution fits very well to the data and yields parameters stable over the samples. We conclude …


Empirical Probability Distribution Of Journal Impact Factor And Over-The-Samples Stability In Its Estimated Parameters, Sudhanshu K. Mishra Feb 2010

Empirical Probability Distribution Of Journal Impact Factor And Over-The-Samples Stability In Its Estimated Parameters, Sudhanshu K. Mishra

Sudhanshu K Mishra

The data on JIFs provided by Thomson Scientific can only be considered as a sample since they do not cover the entire universe of those documents that cite an intellectual output (paper, article, etc) or are cited by others. Then, questions arise if the empirical distribution (best fit to the JIF data for any particular year) really represents the true or universal distribution, are its estimated parameters stable over the samples and do they have some scientific interpretation? It may be noted that if the estimated parameters do not exhibit stability over the samples (while the sample size is large …


A Note On Empirical Sample Distribution Of Journal Impact Factors In Major Discipline Groups, Sudhanshu K. Mishra Feb 2010

A Note On Empirical Sample Distribution Of Journal Impact Factors In Major Discipline Groups, Sudhanshu K. Mishra

Sudhanshu K Mishra

What type of statistical distribution do the Journal Impact Factors follow? In the past, researchers have hypothesized various types of statistical distributions underlying the generation mechanism of journal impact factors. These are: lognormal, normal, approximately normal, Weibull, negative exponential, combination of exponentials, Poisson, Generalized inverse Gaussian-Poisson, negative binomial, generalized Waring, gamma, etc. It is pertinent to note that the major characteristics of JIF data lay in the asymmetry and non-mesokurticity. The present study, frequently encounters Burr-XII, inverse Burr-III (Dagum), Johnson SU, and a few other distributions closely related to Burr distributions to best fit the JIF data in subject groups …