The Master of Science degree program in statistics and analytics is intended to provide training for professional careers, or to serve as a foundation for pursuing a Ph.D. degree. Toward this end, students with degrees other than in mathematics, as well as mathematics majors, are encouraged to apply for admission. Course requirements for this degree may be satisfied by completing course work in one of the following concentrations: Statistics; Business Analytics; Computational Analytics; Educational Statistics & Psychometrics; Quantitative Social Sciences; BioAnalytics; or Operations Analytics. Below are brief descriptions of each of the concentrations.



Students in the Statistics concentration learn the statistical and data analytical methods that are most useful to extract information from data in today’s world. The focus is on applications in a variety of areas, ranging from biostatistics and health sciences, to finance and economics, to marketing, to agriculture. However, the fundamental principles of statistics, and its mathematical foundations, are also stressed. In this way, the student graduating from the statistics concentration is ready to apply today’s statistical tools in industry, business and government, as well as to learn new data analytic methods, keeping up with the rapidly evolving field of statistics and analytics. In addition, the solid theoretical background allows the interested student to continue his or her higher education in a doctoral program.



The goal of operations analytics is to employ quantitative analyses of data, coupled with operations modeling, to transform data in complex systems into better business planning of operations in industry. The principle of industrial engineering and operations research offers advances in operations modeling that can be used to achieve informed and effective decisions to business subjects such as the design of goods and services, managing quality, process, location, layout and routing strategies, supply chain and inventory analysis, healthcare systems, as well as reliability and maintenance of complex systems. This concentration is most appropriate for students with strong mathematics or statistics backgrounds who have a strong interest in the application of those tools in decision making and business planning in real-world industry settings.



The Quantitative Social Science concentration is designed to provide students with a firm theoretical and practical foundation in various quantitative methods that are most widely used for empirical data analysis in social science research. Upon successful completion of study, students will be capable of utilizing some of the most commonly employed knowledge, tools and skills for producing high quality empirical social research. This will ultimately promise students a greater advantage in achieving their professional goals in public, private and non-profit sectors and provide further opportunities for educational attainment in various social science disciplines with a robust methodological base. Interdisciplinary by nature, this concentration also provides sufficient flexibility in curriculum to meet the needs of students with diverse professional backgrounds and motivations.



BioAnalytics is the storage, retrieval, organization and analysis of structured and unstructured data relevant to biological and life sciences. As a concentration, it is most appropriate for those students who either have a degree in mathematics or statistics yet have a strong interest in the biological or life sciences or, conversely, a degree in biological or life sciences but with strong mathematical and/or statistical capabilities. It will be particularly advantageous for those seeking additional quantitative training while pursuing a doctoral degree in biological or other life sciences.



Business Analytics concentration is designed to give business and non-business graduate students knowledge and experience in the management and use of enterprise data for decision-making. The ability to effectively manage and analyze increasingly large and complex sets of data is highly valued among employers in all disciplines, as “business intelligence” becomes a primary source of competitive advantage in many organizations. Students who complete this concentration will have a foundation in the effective management and use of data, the application of statistical decision-making theory and the exploration and exploitation of data using advanced data mining tools and techniques. Students completing this concentration may be eligible to receive a certificate endorsed by the SAS Institute.



The Computational Analytics concentration provides students with knowledge, tools and experience in computational approaches to data analysis to prepare them for careers in industry or government, as well as prepare them for further educational opportunities in the field. As a concentration, it provides flexibility to meet the needs and desires of students from a variety of backgrounds, as well as foster lifelong learning and innovation. This concentration is most appropriate for students with programming and/or statistics training and will be particularly advantageous for those who plan to pursue a doctoral degree in computer science, data science or related fields. Students who complete this concentration will understand principles in data mining, machine learning, artificial intelligence and database and learn state-of-the-art technologies for big data analysis and cloud computing.



Educational statistics and psychometrics involves the design of quantitative research studies, measurement of psychometric and educational constructs and technical skills of data processing for investigating research hypotheses in the fields of educational, social, behavioral and health sciences. Educational and psychological research can be used to a) inform the academic progress of students of all ages, b) evaluate programs, treatments and interventions that impact human behavior, c) predict individual and group outcomes in health, science and other diverse fields and d) model input and output variables for understanding issues and constructs, such as behavior, attitude, health and educational attainment. This concentration is most appropriate for students with mathematics and/or quantitative research training and will be advantageous for those who plan to pursue a doctoral degree in a quantitative research methods or related field.