Six Sigma Practitioner Certificate

12 credit hours

Certificate Flyer (pdf)

Steve Ouellette, Six Sigma Instructor

This certificate is designed to educate students in the advanced statistical tools that are used in business to solve problems and improve product and service quality. The curriculum will focus on the use of basic and advanced statistical techniques and how to use them to identify and achieve improvement opportunities in the real world. Numerous case studies from business and industry will emphasize the connection that applied statistics have to making optimal business decisions.

APPM 5570/EMEN 5005 Introduction to Statistics

Knowing how to generate knowledge from data means that the student understands inferential statistics. This course covers discrete and continuous probability laws, random variables; expectations; laws of large numbers and central limit theory; estimation, testing hypothesis, analysis of variance, regression analysis and nonparametric methods. It emphasizes applications in the business environment with an introduction to packaged computer programs.

APPM 5580/EMEN 5900 Research Methods

Further developing the students’ mastery of statistical analysis, this course begins with how to properly structure and manage research studies. The strengths and weaknesses of commonly used research methods including Analytical, Agreement, Descriptive, and Relational methods are explored and contrasted with Experimental Design. The powerful analysis of variance (ANOVA) statistical technique is introduced. Experimental designs including factor incorporation, nesting, blocking, and controlling are defined as well as how to avoid threats to the internal and external validity of research. Sampling procedures and considerations are also reviewed.

EMEN 5610 Advanced Statistical Methods

This course combines statistical methods with practical applications and computer software.  The students continue to develop expertise in multi-factor ANOVA, including fixed, random, and mixed models and advanced interaction analysis.   The statistical models are implemented and interpreted in the context of actual data sets using available statistical software.

EMEN 5620 Data Mining & Complex Experimental Design

The last course in the sequence combines intermediate and advanced statistical methods with practical research applications. Students learn more advanced measures of correlation and association, simple and multiple linear and non-linear regression modeling, how to design and analyze Fractional Factorial Designs for the solution of common business and industrial research problems, and advanced data mining. The statistical models are implemented and interpreted in the context of actual data sets using available statistical software.  The course concludes the industrial research course sequence with a class project using all of the statistical tools at the students’ disposal to mine an actual data set for significant effects.