Areas of Specialization

The Professional Master's Program in Statistics (MStat) offers individualized programs based on the interests and career objectives of the student:

  • Applied Statistics for Industry
  • Financial Statistics and the Statistics of Risk
  • Bioinformatics, Statistical Genetics, and Biostatistics
  • Statistical Computing and Data Mining
  • Environmental Statistics
  • Joint MBA/MStat Degree Program
  • Preparation for Ph.D. Studies in Statistics, Mathematical Economics, and Finance

Each specialization gives the student an in-depth understanding of the theories behind statistics and prepares them to apply statistics to practical problems in the areas of government, industry and business. They determine how staples of statistics, such as probability theory, inference, regression analysis, clustering, statistical genetics, bioinformatics, etc., can be applied to real-world situations.

Recommended Course Options

Recommended course options for each specialization may be found below:

Applied Statistics for Industry

Statisticians are in demand in all sectors of commerce: manufacturing, distribution, service, non-profit and government. Applications range from quantitative analytics, product creation and testing, quality control, project and enterprise risk management, and a host of other areas. Consider the breadth of application in:

Aerospace/Defense; Auto manufacturers; biotechnology; software and services; chemicals; communication equipment; computer systems; investments; drug manufacturers; electric utilities; food; industrial metals and minerals; airlines; oil and gas; financial services; property and casualty insurance; semiconductors; telecom services; and research and development.

Financial Statistics and the Statistics of Risk

Ultimately, this specialization focuses on the quantitative study of financial markets and their ultimate impact on society; the program emphasizes statistical finance. Statisticians work hand-in-hand with finance specialists, economists, traders, regulators, policy-makers, stakeholders and government/non-government entities (national and international) to try and make sense of the financial labryinth in which we live. Especially today, in addition to quantitative analysis in the financial services industry, statisticians are need in investment/risk management including insurance/reinsurance products, financial engineering, credit analysis and money management.

MStat students can also take advantage of the resources of unique initiatives such as the Center for Computational Finance and Economic Systems (CoFES), which is Rice University's commitment to this important area of intellectual inquiry.

Bioinformatics, Statistical Genetics and Biostatistics

Biostatistics is the science of bringing statistical and probabilistic reasoning to bear on the complex problems presented in research areas such as biology, genetics, human health, medical and environmental science. Biostatisticians play a key and sometimes leading role in the development of new treatment methodologies for human ailments.

Those who want to pursue a career in this highly-interdisciplinary field of statistical genetics and bioinformatics will apply their knowledge of statistics to integrate mathematical, statistical and computer methods to analyze biological, biochemical and biophysical data. There is an urgent need for trained specialists, as recently expressed by Francis Collins, head of the National Institutes of Health, who mentioned "the paucity of trained individuals who are experts in both computational methods and biology."

Our initiatives in this area include:

  • Gene mapping and expression for applications such as causes of cancer and other diseases
  • Developing statistical tools for analysis of massive data sets created by new experimental techniques
  • Developing tools to analyze and correlate genomic data
  • Developing models of biological information
  • Utilizing numerical methods to integrate information at one level to predict functional consequences at another level
Statistical Computing and Data Mining

Statistical computing has revolutionized the field of statistics at the same time the data revolution has transformed business, national security and information processing.

Statisticians must plan for their futures as leaders in visualizing and making inferences from high-dimensional data, processing large data sets using statistical techniques. Those working in these areas must understand the ideas, methods, and tools for analyzing large data sets and techniques for searching for unexpected relationships in data. Topics from supervised and unsupervised learning include regression, discriminant analysis, kernels, model selection, bootstrapping, trees, MARS, boosting, classification, clustering, neural networks, SVM, association rules, principal curves, multidimensional scaling, and projection pursuit.

The emerging field of data mining is a blend of statistics, artificial intelligence, and database research, and can be described as non-trivial process of identifying valid, novel, potentially useful, and ultimately understandable patterns or models or trends in data to make crucial decisions. A mission of the program is to instill in the student the vision and expertise that can prevent statistical computing from being used to unwisely apply statistical methods to reach faulty conclusions. Without a statistical mind-set, data mining is completely inefficient.

Environmental Statistics

Statisticians trained in this area play a number of roles in environmental risk and human health decision making. Demand is high for those who can deliver statistical and mathematical solutions and investigations for the purpose of making environmental decisions. Stochastic models are typically needed for urban and regional air quality, water resources, toxicology and greening. Applications include air, soil and ground water pollution fate and transport, toxicology, risk-based screening levels, exposure concentration/diffusion estimation and risk characterization.

MStat students will have the opportunity to become involved with Rice University's Shell Center for Sustainability, which fosters an interdisciplinary program of research, outreach and education to address actions that can be taken to ensure the sustainable development of communities' living standards, interpreted broadly, to encompass all factors affecting the overall quality of life.

Additional Resources

Joint MBA/MStat Degree Program

At Rice University's Jones Graduate School of Business, MBA students may simultaneously pursue the professional master's in any engineering department, including statistics. For MBA students with a focus in finance, the joint MStat allows students to emphasize statistical finance or general industry tools. This joint program makes especially well-prepared leaders who can handle the business as well as the science side of any industry the student wishes to engage in.

Note that the MStat portion of the joint degree entails at least 24 hours of statistics credit which must be taken in addition to the MBA requirements; 6 hours of the MBA courses should represent significant statistical content. Learn more about the Coordinated MBA/MStat Program.

Preparation for PhD Studies in Statistics, Mathematical Economics and Finance

By successfully completing the MStat degree with this end in mind, the Ph.D. applicant will enjoy a significant advantage when applying to doctoral programs such as Statistics, Mathematical Economics, and Finance. Many times students who choose this specialization register for classes of a more theoretical nature; also, many of the Ph.D. required courses are also taken in the MStat program, opening the student to a greater field of electives as they transition from graduate coursework to a research program.

Stat graduates with this specialization can apply to our Statistics Ph.D. program; however, continuation in the Ph.D. program is NOT automatic. You will need to compete with other applicants on the same footing.