Physical Sciences and Mathematics Commons^™

Semiparametric Regression Analysis Of Bivariate Interval-Censored Data, Naichen Wang

Theses and Dissertations

Survival analysis is a long-lasting and popular research area and has numerous applications in all fields such as social science, engineering, economics, industry, and public health. Interval-censored data are a special type of survival data, in which the survival time of interest is never exactly observed but is known to fall within some observed interval. Interval-censored data arise commonly in real-life studies, in which subjects are examined at periodical or irregular follow-up visits. In this dissertation, we develop efficient statistical approaches for regression analysis of bivariate intervalcensored data, in which the two survival times of interest are correlated and both …

Social Fingerprinting: Identifying Users Of Social Networks By Their Data Footprint, Denise Koessler Gosnell

Doctoral Dissertations

This research defines, models, and quantifies a new metric for social networks: the social fingerprint. Just as one's fingers leave behind a unique trace in a print, this dissertation introduces and demonstrates that the manner in which people interact with other accounts on social networks creates a unique data trail. Accurate identification of a user's social fingerprint can address the growing demand for improved techniques in unique user account analysis, computational forensics and social network analysis.

In this dissertation, we theorize, construct and test novel software and methodologies which quantify features of social network data. All approaches and methodologies are …

Viewing The Moon In Infrared, Kyle Beekman

Statistics

Man has been fascinated by the heavens since ancient times, yet there is still so much that we don’t know. This project was created by Dr. Gary Hughes with goal of obtaining information about the moon and other objects in the vicinity of the Earth. The project was mostly experimental in nature and there was no specific goal at the outset of the project. In the end the project focused on the moon and meteors that traveled through the Earth’s upper atmosphere. Throughout the month of August, students traveled to the Mount Barcroft Research Station in the Eastern Sierras to …

Analyzing Alcohol Behavior In San Luis Obispo, Ariana Montes

Statistics

No abstract provided.

Estimating Prevalence From Complex Surveys, Sophie O'Brien

Masters Theses

Massachusetts passed legislation in the fall of 2012 to allow the construction of three casinos and a slot parlor in the state. The prevalence of problem gambling in the state and in areas where casinos will be constructed is of particular interest. The goal is to evaluate the change in prevalence after construction of the casinos, using a multi-mode address based sample survey. The objective of this thesis is to evaluate and describe ways of using statistical inference to estimates prevalence rates in finite populations. Four methods were considered in an attempt to evaluate the prevalence of problem gambling in …

Quantification Of The Statistical Effects Of Spatiotemporal Processing Of Nontask Fmri Data, M. Muge Karaman, Andrew S. Nencka, Iain P. Bruce, Daniel B. Rowe

Mathematics, Statistics and Computer Science Faculty Research and Publications

Nontask functional magnetic resonance imaging (fMRI) has become one of the most popular noninvasive areas of brain mapping research for neuroscientists. In nontask fMRI, various sources of “noise” corrupt the measured blood oxygenation level-dependent signal. Many studies have aimed to attenuate the noise in reconstructed voxel measurements through spatial and temporal processing operations. While these solutions make the data more “appealing,” many commonly used processing operations induce artificial correlations in the acquired data. As such, it becomes increasingly more difficult to derive the true underlying covariance structure once the data have been processed. As the goal of nontask fMRI studies …

Inferences In Log-Rate Models, Herbert C. Heien, William A. Baumann

Journal of Undergraduate Research at Minnesota State University, Mankato

Log-Rate models are used in analyzing rates of individuals who are exposed to a risk of having a certain characteristic. The explanatory variables could be categorical or in a continuous scale. In finding a Log-Rate Model, parameters are estimated and goodness-of-fit are studied to carefully extract the best model to fit our data. Here we revisit three aspects of Log-Rate Models using the data set give at the end of the paper. The three aspects are parameter estimation, goodness-of-fit of the model, and marginal effect of the factors.

Choosing Between Parametric And Non-Parametric Tests, Russ Johnson

Journal of Undergraduate Research at Minnesota State University, Mankato

A common question in comparing two sets of measurements is whether to use a parametric testing procedure or a non-parametric procedure. The question is even more important in dealing with smaller samples. Here, using simulation, several parametric and nonparametric tests, such as, t-test, Normal test, Wilcoxon Rank Sum test, van-der Waerden Score test, and Exponential Score test are compared.

Modelling Stock Returns In 'Volatility-In-Mean' Framework Under Up And Down Market Movements, Srikanta Kundu Dr.

Doctoral Theses

The first chapter of this thesis begins with a brief review of the existing literature on empirical studies on stock returns, especially those in the context of the relationship between risk and return, at both univariate and multivariate levels. In the next section, studies on the relationship between stock return and monetary policy are reviewed. The motivation of this work is discussed in Section 1.4. Finally, the format of the thesis is given in Section 1.5.A Brief Review of the Literature on Risk-Return Relationship-Both Univariate and Multivariate Cases. In this section, we first present a brief review of this literature …

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 …

Cal Poly Women’S Basketball 2013-2014 Shot Selection Analysis, Noah Alexander Zwarg Mr.

Statistics

The initial goal of my senior project was to find some way to help the Cal Poly women’s basketball team score more efficiently. The first idea that came to my mind on how I could accomplish this goal was to look at the most important thing when it comes to scoring more points, the shot itself. I went with my initial idea and recorded each shot that a player took during the 2013-2014 season and categorized each shot by the distance it was taken (close, medium, long, or three), and whether the shot was open or guarded for a total …

Ranking World Class Chess Players Using Only Results From Head-To-Head Games, Sterling Swygert

Senior Theses

This honors thesis explores a method of ranking the world’s top ten chess grand- masters using only the outcomes of games containing only players in that very set. This method allows for players in a single era to be quickly ranked via algorithmic and numerical means, including very specific information, from a statistical stand- point. Furthermore, unlike the rating systems that are commonly used, the Elo and the Glicko systems, this method is Classicist in its statistical approach, rather than Bayesian. Finally, this ranking method also differs from others as it limits the infor- mation to games between the individuals …

Shopprofiler: Profiling Shops With Crowdsourcing Data, Xiaonan Guo, Eddie C. L. Chan, Ce Liu, Kaishun Wu, Siyuan Liu, Lionel Ni

Research Collection School Of Computing and Information Systems

Sensing data from mobile phones provide us exciting and profitable applications. Recent research focuses on sensing indoor environment, but suffers from inaccuracy because of the limited reachability of human traces or requires human intervention to perform sophisticated tasks. In this paper, we present ShopProfiler, a shop profiling system on crowdsourcing data. First, we extract customer movement patterns from traces. Second, we improve accuracy of building floor plan by adopting a gradient-based approach and then localize shops through WiFi heat map. Third, we categorize shops by designing an SVM classifier in shop space to support multi-label classification. Finally, we infer brand …

Traditional Lecture Versus An Activity Approach For Teaching Statistics: A Comparison Of Outcomes, Jennifer L. Loveland

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Many educational researchers have proposed teaching statistics with less lecture and more active learning methods. However, there are only a few comparative studies that have taught one section of statistics with lectures and one section with activity-based methods; of those studies, the results are contradictory. To address the need for more research on the actual effectiveness of active learning methods in introductory statistics, this research study was undertaken.

An introductory, university level course was divided into two sections. One section was taught entirely with traditional lecture. The other section was taught using active learning methods and a minimal amount of …

Tracing The Evolution Of Active Galactic Nuclei Host Galaxies Over The Last 9 Gyr Of Cosmic Time, A. D. Goulding, W. R. Forman, R. C. Hickox, C. Jones

Dartmouth Scholarship

We present the results of a combined galaxy population analysis for the host galaxies of active galactic nuclei (AGN) identified at 0 < z < 1.4 within the Sloan Digital Sky Survey, Boötes, and DEEP2 surveys. We identified AGN in a uniform and unbiased manner at X-ray, infrared, and radio wavelengths. Supermassive black holes undergoing radiatively efficient accretion (detected as X-ray and/or infrared AGN) appear to be hosted in a separate and distinct galaxy population than AGN undergoing powerful mechanically dominated accretion (radio AGN). Consistent with some previous studies, radiatively efficient AGN appear to be preferentially hosted in modest star-forming galaxies, with little dependence on AGN or galaxy luminosity. AGN exhibiting radio-emitting jets due to mechanically dominated accretion are almost exclusively observed in massive, passive galaxies. Crucially, we now provide strong evidence that the observed host-galaxy trends are independent of redshift. In particular, these different accretion-mode AGN have remained as separate galaxy populations throughout the last 9 Gyr. Furthermore, it appears that galaxies hosting AGN have evolved along the same path as galaxies that are not hosting AGN with little evidence for distinctly separate evolution.

Student Fact Book, Fall 2014 - Thirty-Eighth Annual Edition, Wright State University, Office Of Student Information Systems, Wright State University

Wright State University Student Fact Books

The student fact book has general demographic information on all students enrolled at Wright State University for Fall Semester, 2014.

Flint International Statistics Conference Announcement, Kettering University

Flint: One City, 100 Years of Variability

CONFERENCE ANNOUNCEMENT POSTER:

Kettering University is organizing this international conference to celebrate the IYS 2013 and the 175th anniversary of the American Statistical Association.

The main focus of this conference will be on STATISTICAL METHODS & STUDIES OF HISTORICAL DATA.

Participants may use any data. Data on Flint—consisting of up to 100 years of demographic, health, labor, census and crime records will be summarized and made available to participants. Sessions will include presentations of the statistical achievements and perspectives, followed by several talks on current results.

Lack Of Quantitative Training Among Early-Career Ecologists: A Survey Of The Problem And Potential Solutions, F. Barraquand, T. G. Ezard, P. Søgaard Jørgensen, Naupaka B. Zimmerman, S. Chamberlain, R. Salguero-Gómez, T. J. Curran, T. Poisot

Biology Faculty Publications

Proficiency in mathematics and statistics is essential to modern ecological science, yet few studies have assessed the level of quantitative training received by ecologists. To do so, we conducted an online survey. The 937 respondents were mostly early-career scientists who studied biology as undergraduates. We found a clear self-perceived lack of quantitative training: 75% were not satisfied with their understanding of mathematical models; 75% felt that the level of mathematics was “too low” in their ecology classes; 90% wanted more mathematics classes for ecologists; and 95% more statistics classes. Respondents thought that 30% of classes in ecology-related degrees should be …

Methods For Clustering Mixed Data, Jeanmarie L. Hendrickson

Theses and Dissertations

We give a brief introduction to cluster analysis and then propose and discuss a few methods for clustering mixed data. In particular, a model-based clustering method for mixed data based on Everitt's (1988) work is described, and we use a simulated annealing method to estimate the parameters for Everitt's model. A penalized log likelihood with the simulated annealing method is proposed as a remedy for the parameter estimates being drawn to extremes. Everitt's approach and the proposed method are compared based on their performance in clustering simulated data. We then use the penalized log likelihood method on a heart disease …

Building A Predictive Model For Baseball Games, Jordan Robertson Tait

All Graduate Theses, Dissertations, and Other Capstone Projects

In this paper, we will discuss a method of building a predictive model for Major League Baseball Games. We detail the reasoning for pursuing the proposed predictive model in terms of social popularity and the complexity of analyzing individual variables. We apply a coarse-grain outlook inspired by Simon Dedeos' work on Human Social Systems, in particular the open source website Wikipedia [2] by attempting to quantify the influence of winning and losing streaks instead of analyzing individual performance variables. We will discuss initial findings of data collected from the LA Dodgers and Colorado Rockies and apply further statistical analysis to …