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Program Overview

Our Program

The curriculum is designed for students who plan to enter business, industry, or government as statisticians; to become professional actuaries; or to continue on to graduate school in statistics/ biostatistics or another field where quantitative ability is valuable (operations research, medicine, public health, demography, psychology, etc.). Students can choose to undertake special projects to gain experience in data analysis, design, and statistical computing. Also, experience may be gained with local industry and other organizations for those interested in quality control, industrial statistics, survey and market research or forecasting, for example.

Why Statistics

Statistics is a mathematical science extensively used in a wide variety of fields. Indeed, every discipline which gathers and interprets data uses statistical concepts and procedures to understand the information implicit in their data. Statisticians become involved in efforts to solve real world problems by designing surveys and experimental plans, constructing and interpreting descriptive statistics, developing and applying statistical inference procedures, and developing and investigating stochastic models or computer simulations. To investigate new statistical procedures requires a knowledge of mathematics and computing as well as statistical theory. To apply concepts and procedures effectively also calls for an understanding of the field of application.

Curriculum

Statistics Curricular Themes

Mathematics and statistics permeate modern life. The study of these subjects leads to the acquisition of new knowledge, new skills and a new language for communication. Below we outline the general curricular themes we see as common to all of our programs. Precise learning outcomes that are consistent with these themes and that are feasible to evaluate have been incorporated into our departmental learning outcomes.

Universality: We hope to impart an appreciation for the power, beauty and breadth of mathematics and statistics. On one extreme, theoretical mathematics and statistics are beautiful subjects that require strong skills in critical and abstract thinking. The simple abstract concepts that arise in these subjects, such as a vector or a rate of change, have been applied to the immeasurable benefit of society in all areas of human endeavors. These applied areas serve to motivate and inspire new theoretical research.

Communication: Effective communication is an essential skill in all parts of life, from the person to the professional and from the humanities to the sciences. Practicing precision and clarity in effective mathematical communication, both verbally and visually, is excellent training for oral and written communications in all fields.

Problem solving: Solving a problem, whether in mathematics and statistics or elsewhere, requires a clear delineation of the problem, requisite knowledge, relevant skills and creativity.

Computational skills: Computing, grounded in paper-and-pencil work, runs the gamut from order-of-magnitude estimates in one’s head to the ability to use a computer to provide insight into a problem. These skills are especially important in those disciplines more directed toward modeling.

Curriculum checksheets (CEMS student services)

The core curriculum, major and ancillary courses, and related requirements are detailed in the ¶¶Òõ̽̽ Undergraduate Catalogue.

Outcomes

Statistics Learning Outcomes (Major in Statistics, B.S. in Mathematical Sciences)

The Statistics program is committed to preparing our majors for success in the workplace and in graduate studies with focus on achieving these learning outcomes:

• Graduates should be able to critically evaluate the strengths and weaknesses of study designs and can select a study design that is appropriate for addressing a specific research question.
• Graduates should be able to use statistical reasoning, formulate a problem in statistical terms, perform exploratory analysis of data by graphical and other means, and carry out a variety of formal inference procedures.
• Graduates should be able to describe important theoretical results and understand how they can be applied to answer statistical questions.
• Graduates should have familiarity with a standard statistical software packages and encourage study of data management and algorithmic problem solving.
• Graduates should have strong communication skills which are necessary to effectively collaborate as part of interdisciplinary teams including the ability to interpret and communicate the results of a statistical analysis through oral and written reports.

More

Handbook for Mathematics and Statistics Majors (PDF)