Actuaries work with all kinds of organizations to analyze data, assess risk, and estimate the probability and likely cost of occurrences such as death, sickness, injury, disability or loss of property. The Master of Science in Actuarial Science degree program educates future leaders of the actuarial industry by training them in actuarial theory and methods across a wide spectrum of actuarial applications involving probabilistic and statistical models.

The program offers students a wide variety of specialized courses in actuarial science, probability and statistics, financial mathematics, decision theory, economics and other related fields. Taught by top-tier faculty at The University of Texas at Dallas, Actuarial Science graduates have the proficiencies they need to take the seven professional actuarial examinations administered by the Society of Actuaries (SOA) and the Casualty Actuarial Society (CAS) and to serve as actuaries in fields such as accounting, finance, insurance, consulting, government and emerging markets. The University of Texas at Dallas is recognized as the Society of Actuaries (SOA) Center of Actuarial Excellence (CAE), the highest level of SOA recognition for universities.

How does a statistician design an experiment to test a new drug? What is an efficient algorithm to solve a differential equation, and when does it work? How do you determine a fair price for an annuity? Given a complex network of nodes and edges, what is the shortest path from one vertex to another? How can you teach problem solving in a diverse high school classroom? These are only some of the questions to be explored in our four graduate program concentrations. 

At SIUE, we have a graduate student-to-faculty ratio of two-to-one, so our students receive personalized attention from faculty recognized for outstanding teaching and excellent research. The Department of Mathematics and Statistics at SIUE provides learning and research opportunities in many areas and students are exposed to various cultures from diverse faculty members in the College of Arts and Sciences.

The graduate program in Applied Statistics is designed to prepare students to join twenty-first century business and industry in their growing needs for statistical analyses. An optimal mix of mathematical and computational background also enables the graduates to contribute effectively in the educational institutions. A Common Core course is waived if credit has been received for an equivalent course with grade of C or better at the undergraduate or graduate levels. All Required Common Core courses, or their equivalents, must be completed before graduation. College of Graduate Study and Research Transfer policy applies

The Master of Science in statistics has a unique focus, with courses that prepare students for professional careers in consulting, research and academia or more advanced study. This program is designed to offer you the skills you need to become immediately hirable statisticians.

The M.S. degree in Statistics is designed to provide individuals with the academic foundation needed to pursue doctoral studies; to prepare competent statisticians who are equipped to accept responsibilities in business, industry, and public service positions; and to present a supplemental graduate program for students specializing in areas where statistics are readily used, such as social sciences, criminal justice, and the physical sciences. Core classes include mathematical statistics, regression analysis, multivariate analysis, and experimental design.

Our department features small classes and collaborative relationships with industry partners. Working with the same data software programs that employers are looking for, you’ll build crucial skills in data visualization, predictive modeling and data analysis techniques.

Through the master's in Applied Statistics at UND, you’ll gain:

Competency in high level statistics including:

Problem solving

Data analysis

Data science and data mining

Machine learning

Big data

The range of skills required to carry out programs of independent research as a data scientist

The ability to effectively use a variety statistical software packages such as Python, SAS and R

Analytical skills needed to work as a professional data applied statistics scientist

The Department of Economics and Decision Sciences offers courses leading to the Master of Science degree in Applied Statistics and Decision Analytics. Further information concerning the program and areas of specialization may be obtained from the department chairperson.
The Master of Science in Applied Statistics and Decision Analytics is a multidisciplinary graduate degree program with a unique focus on applied statistics and decision analytics. This program is intended for graduates from undergraduate programs in the quantitative and biological sciences, mathematics, sociology, psychology, business, computer sciences, physics, engineering, and education, as well as working professionals desiring to sharpen their data-analysis and analytical skills and learn advanced statistical methods. The 30-semester-hour curriculum provides students with a firm foundation of statistical analysis and modeling commonly used in many fields, including education, science, technology, health care, government, business, or social science research. The graduates of the program will be trained on industry-standard software packages, such as SAS and/or R, and gain modern analytical skills that are sought after in many fields, particularly in the areas of business and decision analytics or data analytics. The program is designed to include 18 semester hours (s.h.) of core courses, 6 s.h. of directed electives, and 6 s.h. from one of the following: a thesis option, an internship option, or an all coursework option.

The Applied Statistics M.S. program is designed to advance students pursuing a statistics-oriented career in industries where basic statistical skills and knowledge of contemporary methods of data analysis and modeling are required.
 
Additionally, for graduate students who intend to pursue a doctoral degree in Applied Probability and Statistics, the M.S. program will equip them with the basic training in foundations needed for further graduate studies and independent research. It will also benefit practicing engineers and professionals seeking to advance their knowledge of statistical methods.
 
We expect that students and/or graduates of the Applied Statistics M.S. program will exhibit and/or engage in:

• Professionalism: Our students work on developing leadership, collaboration, networking and other professional skills that are needed by today’s top statisticians.
• Academic Excellence: Our students will be passionate about advancing their knowledge of statistical methods to become an asset in fields such as medicine and pharmaceuticals, environmental sciences, finance, government and market research.
• Solve Real-world Problems: Our students will specialize in methods for collecting data by sampling methods and in statistical modeling and analysis, with a view to drawing meaningful conclusions from data.

Students in the Master of Science in Biostatistics program gain the skills necessary to apply statistical, mathematical, and computational techniques to scientific research in health-related fields, including medicine, epidemiology, and public health. Biostatistics is an integral and indispensable tool in improving health and reducing illness. Biostatisticians play essential roles in designing studies and analyzing research data. Graduates are employed in public health research and service organizations, university research groups, hospitals, pharmaceutical companies, health-related industries, and government. The demand for biostatisticians in the job market has been consistently strong. New technologies are generating an unprecedented amount of data which present exciting opportunities for biostatisticians with strong computational skills.

The program provides students with a thorough understanding of biostatistical methods, strong computational skills, and the ability to apply this knowledge to research focusing on health-related problems. The program prepares students to handle the quantitative and computational aspects of a research project including study design, data collection and management, developing analysis plans, conducting analyses, and reporting findings both orally and in writing. Coursework includes statistical theory and methods, computing and data management, epidemiology, and general public health topics. Incorporated into the second year is a two quarter-long practicum experience working on a real academic, government, or industry project in a sponsoring organization setting. The practicum-based research project will involve the application of biostatistical analysis to a problem of significance to the sponsoring academic, government, or industry organization with joint oversight provided by a Department faculty member and an on-site PhD-level biostatistician.

Learning Outcomes

Graduates will be able to:

1. understand the mathematical and statistical theory that underlies commonly used statistical methods;
2. choose appropriate statistical methods for data analysis;
3. correctly and effectively implement descriptive and inferential statistical methods;
4. identify and criticize inappropriate use of statistics;
5. consult with non-statisticians to help collect and analyze data; and
6. acquire effective communication skills for disseminating statistical findings.