Browsing Statistics by Title
Now showing items 58-77 of 123
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Frost Depth Prediction
(North Dakota State University, 2014)The purpose of this research project is to develop a model that is able to accurately predict frost depth on a particular date, using available information. Frost depth prediction is useful in many applications in several ... -
A Geostatistical Analysis of Housing Prices in Fargo
(North Dakota State University, 2017)This study investigated housing prices by applying geostatistical regression techniques to identify the significant factors affecting residential housing sales prices in Fargo, North Dakota. The study used a subset of ... -
Graph two-sample test via empirical likelihood
(North Dakota State University, 2024)In the past two decades, there has been a notable surge in network data. This proliferation has spurred significant advancements in methods for analyzing networks across various disciplines, including computer science, ... -
Identification of Differentially Expressed Genes and Gene Sets Using a Modified Q-Value
(North Dakota State University, 2014)Gene expression technologies allow expression levels to be compared across treatments for thousands of genes simultaneously. Statistical methods exist for identifying differentially expressed (DE) genes and gene sets while ... -
Identification of Differentially Expressed Genes When the Distribution of Effect Sizes is Asymmetric in Two Class Experiments
(North Dakota State University, 2017)High-throughput RNA Sequencing (RNA-Seq) has emerged as an innovative and powerful technology for detecting differentially expressed genes (DE) across different conditions. Unlike continuous microarray data, RNA-Seq data ... -
Identifying Significant Factors Influencing Metabolic Syndrome In China
(North Dakota State University, 2015)Metabolic Syndrome occurs when a person’s body does not properly use and store energy. The disease has five criteria: abdominal obesity, insulin resistance, hypertension, dyslipidemia, and impaired glucose regulation. The ... -
The Influence of Race, Age, Comorbidities, and BMI on Disability Following Stroke in Elderly People Living in Their Own Home
(North Dakota State University, 2020)Stroke is one of the major health issues in the United States. I explored different aspects of disability based on a history of stroke, race, comorbidities, age, and body mass index for the population of community dwelling ... -
Information Asymmetry in Budget Allocation: An Analysis of the Truth-Inducing Incentive Scheme
(North Dakota State University, 2016)Truth-inducing incentive schemes are used to motivate project managers to provide unbiased project information to portfolio manager to reduce information asymmetry between portfolio manager and project managers. To improve ... -
Integrative Data Analysis of Microarray and RNA-seq
(North Dakota State University, 2018)Background: Microarray and RNA sequencing (RNA-seq) are two commonly used high-throughput technologies for gene expression profiling for the past decades. For global gene expression studies, both techniques are expensive, ... -
Investigating Gender Bias Among Grant Applicants
(North Dakota State University, 2020)An ongoing debate in society is about the existence of a wage gap between genders, and society’s alleged preference to hire a man over an equally qualified woman. This debate extends from the commercial employment world ... -
Investigating Statistical vs. Practical Significance of the Kolmogorov-Smirnov Two-Sample Test Using Power Simulations and Resampling Procedures
(North Dakota State University, 2018)This research examines the power of the Kolmogorov-Smirnov two-sample test. The motivation for this research is a large data set containing soil salinity values. One problem encountered was that the power of the ... -
Investment Behavior Analysis Based on Tail Risk Management
(North Dakota State University, 2018)As behavioral finance is becoming more prevalent in academic area, a study is worth conducting to pinpoint investors’ preference through managing tail risk of asset portfolios. This study investigates investors’ investment ... -
Linear Modeling of Election Results for U.S. House of Representatives Candidates and State Executive Offices for Iowa, Minnesota, and North Dakota
(North Dakota State University, 2020)Better understanding the relationship between the results for the U.S. House of Representatives and for state executive offices could potentially be useful in predicting outcomes if a significant relationship is present ... -
Loss Reserving Chain Ladder Methods Applied to a Small Midwestern Insurance Company
(North Dakota State University, 2015)Estimating future losses is integral to setting aside appropriate reserves in the insurance industry. This study analyzes different Chain Ladder reserving methods based on weighted-least square regression that consider ... -
Mass Spectrum Analysis of a Substance Sample Placed into Liquid Solution
(North Dakota State University, 2011)Mass spectrometry is an analytical technique commonly used for determining elemental composition in a substance sample. For this purpose, the sample is placed into some liquid solution called liquid matrix. Unfortunately, ... -
Measuring Performance of United States Commercial and Domestic Banks and its Impact on 2007-2009 Financial Crisis
(North Dakota State University, 2019)In the analysis of efficiency measures, the statistical Stochastic Frontier Analysis (SFA) and linear programming Data Envelopment Analysis (DEA) estimators have been widely applied. This dissertation is centered around ... -
A Model to Predict Matriculation of Concordia College Applicants
(North Dakota State University, 2017)Colleges and universities are under mounting pressure to meet enrollment goals in the face of declining college attendance. Insight into student-level probability of enrollment, as well as the identification of features ... -
Model Validation and Diagnostis in Right Censored Regression
(North Dakota State University, 2013)When censored data are present in the linear regression setting, the Expectation-Maximization (EM) algorithm and the Buckley and James (BJ) method are two algorithms that can be implemented to fit the regression model. We ... -
Modeling Loss Severity With Lognormal Mixtures
(North Dakota State University, 2015)Property and Casualty insurance companies set premium rates by evaluating both loss fre- quency and loss severity data. Insurance companies often model severity using a well-known single distribution such as Lognormal ... -
Modeling the Winners of NCAA Women's Division II Basketball Tournament Games
(North Dakota State University, 2016)This thesis first presents a least squares regression model to identify the in-game statistics that help explain the variation in point spread for NCAA Division II Women’s Basketball Tournament games. Then a logistic ...