Many rating systems exist that order the Division I teams in Men's College Basketball that compete in the NCAA Tournament, such as seeding teams on an S-curve, and the Pomeroy and Sagarin ratings, simplifying the process of choosing winners to a comparison of two numbers. Rather than creating a rating system, we analyze each matchup by using the difference between the teams' individual regular season statistics as the independent variables. We use an MCMC approach and logistic regression along with several model selection techniques to arrive at models for predicting the winner of each game. When given the 63 actual games in the 2012 tournament, eight of our models performed as well as Pomeroy's rating system and four did as well as Sagarin's rating system when given the 63 actual games. Not allowing the models to fix their mistakes resulted in only one model outperforming both Pomeroy and Sagarin's systems. / McAnulty College and Graduate School of Liberal Arts / Computational Mathematics / MS / Thesis

Sample size calculation methods for ordinal logistic regression are proposed to test statistical hypotheses. The author was motivated to do this work by the need for statistical analysis of the red imported fire ants data. The proposed methods use the concept of approximation by the moment-generating function. Some correction methods are also suggested. When a prior data set is available, an empirical method is explored. Application of the proposed methodology to the fire ant mating flight data is demonstrated. The proposed sample size and power calculation methods are applied in the hypothesis testing problems. Simulation studies are also conducted to illustrate their performance and to compare them with existing methods.

Today's young people are well-educated ever but in a poor employment situation. At the beginning of this paper, I first state the situation both in the world and in China, revealing the poor employment situation of youth. Then I introduce systems related to youth employment in China and measures the government taken to help graduate students to find a job. The purpose of this paper is to analyze employment of youth people in China especially among the medium and highly educated people and find which and how the factors contribute to it. By using the Logistic Regression by STATA, I find that the main factors are gender, age, living area, and political status, major and educational level. The result reveals that the discrimination and gap between rural and urban area are severe issues in China. Last but not least, I give some suggestions both to the society and the individual to improve the youth employment.

This research focuses on characterizing a potato with extra sugar content and identifying the location and depth of the extra sugar content using the active thermography imaging technique. The extra sugar content of the potato is an important problem for potato growers and potato chip manufacturers. Extra sugar content could result in diseases or wounds in the potato tuber. In general, potato tubers with low sugar content are considered as having a higher quality. The inspection system and general methodologies characterizing extra sugar content will be presented in this study. The average heating rate obtained from the thermal image analysis is the major factor in characterization procedures. Using information on the average heating rate, the probability of achieving a potato with extra sugar content may be predicted using the logistic regression model. In addition, neural networks are also used to identify the potato with extra sugar contents. The correct rate for identifying a potato with extra sugar content in it can reach 85%. The location of extra sugar content can also be found using the logistic regression model. Results show the overall correct rate predicting the extra sugar content location with a resolution of 20 by 20 pixels is 91%. In predicting the extra sugar content depth, amounts exceeds 2/3 inches are not detectable by analyzing thermal images. The depth of extra sugar content can be discriminated in 0.3 inch increments with a high rate of accuracy (87.5%).

The relationship between precipitation and large-flow is important to understand and characterize in the climate system. We examine statistical relationships between the Tropical Rainfall Measurement Mission (TRMM) 3B42 gridded precipitation and large-scale ow variables in the Tropics for 2000{2007. These variables include NCEP/NCAR Re-analysis sea surface temperatures (SSTs), vertical temperature pro files, omega, and moist static energy, as well as Atmospheric Infrared Sounder (AIRS) vertical temperatures and QuikSCAT surface divergence. We perform correlation analysis, empirical orthogonal function analysis, and logistic regression analysis on monthly, pentad, daily and near-instantaneous time scales. Logistic regression analysis is able to incorporate the non-linear nature of precipitation in the relation- ship. Flow variables are interpolated to the 0.25 degrees TRMM 3B42 grid and examined separately for each month to o set the effects of the seasonal cycle. January correlations of NCEP/NCAR Re-analysis SSTs and TRMM 3B42 precipitation have a coherent area of positive correlations in the Western and Central Tropical Pacific on all time scales. These areas correspond with the South Pacific Convergence Zone (SPCZ) and the Inter Tropical Convergence Zone (ITCZ). 500mb omega is negatively correlated with TRMM 3B42 precipitation across the Tropics on all time scales. QuikSCAT divergence correlations with precipitation have a band of weak and noisy correlations along the ITCZ on monthly time scales in January. Moist static energy, calculated from NCEP/NCAR Re-analysis has a large area of negative correlations with precipitation in the Central Tropical Pacific on all four time scales. The first few Empirical Orthogonal Functions (EOFs) of vertical temperature profiles in the Tropical Pacific have similar structure on monthly, pentad, and daily timescales. Logistic regression fit coefficients are large for SST and precipitation in four regions located across the Tropical Pacific. These areas show clear thresholded behavior. Logistic regression results for other variables and precipitation are less clear. The results from SST and precipitation logistic regression analysis indicate the potential usefulness of logistic regression as a non-linear statistic relating precipitation and certain ow variables.

The wellness of credit risk has great influence on the Value of Mortage-Backed Securities (MBS), but there isn¡¦t any valuator to supervise and to estimate these securities-issued institutions in Taiwan. For earning the trust of the masses, these institutions must have great abilities to control credit risk in an acceptable degree, and then the people will be willing to invest in these MBS. This research makes use of data totaling 20,576 cases (17,425 normal cases and 3,151 default cases) from a certain domestic bank, Bank P, and constructs the Logistic Regression Model to steer the substantial evidence research. With the right prediction of 96.7% in normal, 85.4% in default, and 95% in whole, we find that we can use the borrower¡¦s age, occupation, the object of collateral, the use of collateral, the loan purpose, the year of loan, the line of credit, the category of interest, the interest rate, the source of case and the branch office as key factors for credit risk appraisal of reference provided to banks. In this study, we will determine whether interest rate is the key factor for default, followed by occupation. The other two factors, the category of interest and the source of case, which are not popularly talked about in related studies, are confirmed as the remarkable influence factors for credit risk. The other important discovery is that the influence of the loan condition and the specialities of the collateral have greater impact on credit risk than the personality of the borrower. This research provides some reference for financial institutions on credit evaluation, and makes up a good model for credit control. For previously issued MBS, this research also provides some academic basis for future adaptation.

This study includes six dimensions: article¡¦s attributions, author¡¦s traits, the identities of censors, the opinions of censors, the results of judgment and the processes of publication; uses content analysis to describe the present editorial situation of Journal of Human Resource Management (JHRM) and constructs the regression model by the logistic regression using four dimensions except the results of judgment and the processes of publication. The findings indicate two sides, the first one is on the content analysis: it has a significant difference between the year of contribution and references, article¡¦s issue, total pages, number of authors, days from submission to acceptance, days from submission to publication; and different academic title also affect the article¡¦s research method. The second one is on the effect factor of the article is published or not: article¡¦s attributions and author¡¦s traits, including 16 variables, have no any effects on the acceptance of an article, but the identities of censors and the opinions of censors, including 8 variables, do have significant effects on it. The important factors to the article are the number of censors, the application of entirety, the innovation of deliverance and the completeness of viewpoint and as the order for influencing the acceptance of an article.

In the thesis, we study the data collected from VICU of Kaohsiung Veterans General Hospital.The data consists of the following two kinds. The data of the first kind is ten minute ECG data with sampling frequency 500Hz. The data of the second kind is long term one minute average heart rate. There are two main topics studies in this thesis. In the first part, we consider the standard deviations which be taked log and medians of RR intervals, PR intervals and RT intervals, respectively derived from first kind data. By considering the odds ratio¡Bsensitivity and specificity, and we select the heart classification vectors. The object is to classify among normal and ventricular heart disease (VSD), normal and ventricular heart disease with congestive heart failure (VSD+CHF). We proposed a method of both variables and two-step classification procedure. Furthermore, we built the logistic regression models. In the second part, we derive the distribution of the spectrum power ratio of low frequency to high frequency. Shewhart control chart and Tabular cusum chart are constructed to monitor RG. Also, we discover the periodicity of RG. Finally, there exists positive correlation between RA¡]or RG¡^ and autocorrelation of lag one of RR interval.

Sample size calculation methods for ordinal logistic regression are proposed to test statistical hypotheses. The author was motivated to do this work by the need for statistical analysis of the red imported fire ants data. The proposed methods use the concept of approximation by the moment-generating function. Some correction methods are also suggested. When a prior data set is available, an empirical method is explored. Application of the proposed methodology to the fire ant mating flight data is demonstrated. The proposed sample size and power calculation methods are applied in the hypothesis testing problems. Simulation studies are also conducted to illustrate their performance and to compare them with existing methods.

<p>Today's young people are well-educated ever but in a poor employment situation. At the beginning of this paper, I first state the situation both in the world and in China, revealing the poor employment situation of youth. Then I introduce systems related to youth employment in China and measures the government taken to help graduate students to find a job. The purpose of this paper is to analyze employment of youth people in China especially among the medium and highly educated people and find which and how the factors contribute to it. By using the Logistic Regression by STATA, I find that the main factors are gender, age, living area, and political status, major and educational level. The result reveals that the discrimination and gap between rural and urban area are severe issues in China. Last but not least, I give some suggestions both to the society and the individual to improve the youth employment.</p>