Statistics: Recent submissions
Now showing items 101-120 of 123
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Development of a Prediction Model for the NCAA Division-I Football Championship Subdivision
(North Dakota State University, 2013)This thesis investigates which in-game team statistics are most significant in determining the outcome in a NCAA Division-I Football Championship Subdivision (FCS) game. The data was analyzed using logistic and ordinary ... -
Examining Influential Factors and Predicting Outcomes in European Soccer Games
(North Dakota State University, 2013)Models are developed using least squares regression and logistic regression to predict outcomes of European soccer games based on four variables related to the past k games of each team playing with the following values ... -
Comparing Dunnett's Test with the False Discovery Rate Method: A Simulation Study
(North Dakota State University, 2013)Recently, the idea of multiple comparisons has been criticized because of its lack of power in datasets with a large number of treatments. Many family-wise error corrections are far too restrictive when large quantities ... -
An Analysis of Factors Contributing to Wins in the National Hockey League
(North Dakota State University, 2013)This thesis looks at common factors that have the largest impact on winning games in the NHL. Data was collected from regular season games for all teams in the NHL over seven seasons. Logistic and least squares regressions ... -
Analysis of Significant Factors in Division I Men's College Basketball and Development of a Predictive Model
(North Dakota State University, 2013)While a number of statistics are collected during an NCAA Division I men’s college basketball game, it is potentially of interest to universities, coaches, players, and fans which of these variables are most significant ... -
On K-Means Clustering Using Mahalanobis Distance
(North Dakota State University, 2012)A problem that arises quite frequently in statistics is that of identifying groups, or clusters, of data within a population or sample. The most widely used procedure to identify clusters in a set of observations is known ... -
Entropy as a Criterion for Variable Reduction in Cluster Data
(North Dakota State University, 2012)Entropy is a measure of the randomness of a system state. This quantity gives us a measure of uncertainty that is associated with each particular observation belonging to a specific cluster. We examine this property and ... -
Nonparametric Test for the Umbrella Alternative in a Randomized Complete Block and Balanced Incomplete Block Mixed Design
(North Dakota State University, 2012)Nonparametric tests have served as robust alternatives to traditional statistical tests with rigid underlying assumptions. If a researcher expects the treatment effects to follow an umbrella alternative, then the test ... -
Forecasting Point Spread for Women’s Volleyball
(North Dakota State University, 2016)Volleyball has become a well-known and competitive sport with physical and technical performances over the years. The game results are determined by some important factors such as players, and the team’s skills to succeed ... -
Prediction of the World Cup Soccer Winner: Using Two Statistical Methods
(North Dakota State University, 2016)Soccer is considered the most popular sport on earth and applying statistical models to analyze small soccer data has been of a keen interest to modern researchers. Statistical modeling of soccer data also provides guidance ... -
Boundary Estimation
(North Dakota State University, 2015)The existing statistical methods do not provide a satisfactory solution to determining the spatial pattern in spatially referenced data, which is often required by research in many areas including geology, agriculture, ... -
Comparing Several Modeling Methods on NCAA March Madness.
(North Dakota State University, 2015)This year (2015), according to the AGA’s (American Gaming Association) research, nearly about 40 million people filled out about 70 million March Madness brackets (Moyer, 2015). Their objective is to correctly predict the ... -
Clustering Algorithm Comparison for Ellipsoidal Data
(North Dakota State University, 2015)The main objective of cluster analysis is the statistical technique of identifying data points and assigning them into meaningful clusters. The purpose of this paper is to compare different types of clustering algorithms ... -
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 ... -
A Comparison of False Discovery Rate Method and Dunnett's Test for a Large Number of Treatments
(North Dakota State University, 2015)It has become quite common nowadays to perform multiple tests simultaneously in order to detect differences of a certain trait among groups. This often leads to an inflated probability of at least one Type I Error, a ... -
Proposed Nonparametric Tests for the Simple Tree Alternative in a Mixed Design
(North Dakota State University, 2014)Video summarizing Ph.D. dissertation for a non-specialist audience. -
Comparison of Classification Rates among Logistic Regression, Neural Network and Support Vector Machines in the Presence of Missing Data
(North Dakota State University, 2014)Statistical models such as Logistic Regression (LR), Neural Network (NN) and Support Vector Machines (SVM) often use datasets with missing values while making inferences regarding the population. When inferences are made ... -
An Application of Simplicial Intercept Depth (SID) Method for Fitting Linear Models
(North Dakota State University, 2014)This paper presents an application based on the Simplicial Intercept Depth method introduced by Liu (2004). We use this method to get the best linear fit of the phenotypic data for spot blotch resistant reaction of two ... -
Ds-Optimal Design for Model Discrimination in a Probit Model
(North Dakota State University, 2014)In toxicology studies, dose response functions with a downturn at higher doses are often observed. For such response functions, researchers often want to see if the downturn of the response is signifcant. A probit model ... -
Bracketing NCAA Men's Division I Basketball Tournament
(North Dakota State University, 2013)This paper presents a new bracketing method for all 63 games in the NCAA Division 1 basketball tournament. This method, based on the logistic conditional probability models, is self-consistent in terms of constructing ...