Courses

This course encompasses the techniques and tools needed for the development, investigation, and demonstration of competence in conducting qualitative research in mathematics education. Principles of qualitative data analysis are a significant focus of the course, with particular attention given to specific methods used to code and analyze data.

This course examines current issues in quality improvement and patient safety activities. The course includes a review of past and current efforts, tools, and theories of quality assessment, assurance, utilization management, and measuring and improving outcome. In addition, the course looks at new initiatives to improve quality and safety through regulation, reporting and financial incentives.

This capstone course uses advanced statistical quality tools such as autocorrelated data, multi-variate quality controls charts, response surface methodology, ridge analysis, and evolutionary operations (EVOP). Advanced Six Sigma concepts will be taught and students will have the opportunity to earn a Black Belt in Six Sigma upon successful completion of the certification exam and an acceptable project.

This course provides in-depth knowledge in reliability modeling and maintenance optimization for components and systems. The course also covers advanced quality control techniques including multivariate process control. Methodologies are applied to solve practical problems arising from various industry domains. Restricted to students enrolled in the MS Engineering program.

This course mainly covers regression, a powerful and widely used data analysis technique. This course is designed for advanced graduate students who intend to use regression and related methods to address research questions. Student will learn the regression model's underlying statistical ideas and use regression to analyze various complicated real- word problems. Heavy emphasis will be placed on the analysis of actual datasets.

LAB. 1. Pr. STAT 7000. Study of the application of linear regression analysis to business research. First advanced course in applied linear statistics models. STAT 7000 or approved equivalent.

or approved equivalent. Study of the application of linear regression analysis to business research. First advanced course in applied linear statistics models.

or approved equivalent. Third course in statistical modeling. Emphasis on applications of Principal Components Analysis, and Structural Equation Modeling to management research.

How to mathematically and statistically model geographic problems is the focus of this course. The application of multivariate statistical techniques to geographic problems and the problems that spatial data create in the application of statistical and other quantitative techniques are central issues.

Application of advanced statistical procedures including multivariate techniques for analysis of point and areal patterns and spatial data.