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Quantitative Studies
This concentration offers students interested in mathematics, statistics, computer science, or other quantitative methods the opportunity to apply these methods to the study of a wide variety of phenomena, which originate in the natural or social sciences, or, for that matter, in the arts or in the study of languages and literature.
It develops competence in quantitative methods, problem-solving skills, ability to interpret and communicate quantitative results, and understanding of applications of quantitative analysis. The concentration prepares graduates for future training or careers in mathematics, computer science, actuarial sciences, education, medicine, law, and economics, among others. The goal of the Quantitative Studies concentration is to provide the student with an opportunity to observe and participate in the dialogue between two fields of study which may have very different modes of thought, but find certain problems of common interest. The Senior Thesis is the natural culmination of this process, and it is strongly suggested that the student’s thesis be on a topic associated with this concentration.
Related Career Paths
Students with a concentration in quantitative studies may enter into fields such as business, management, statistics, information technology, and consulting.
Curriculum
The minimum requirements are one course in statistics, 12 credits of intermediate courses, one year-long sequence in mathematics at the 300-level, and two courses at the 300-level or above in the area of application. 28 credits overall is required. There are no limits to the suitable areas of application. Art, music, literature, biology, chemistry, physics, economics, political science, psychology, or sociology—any of these would do if the student looked at issues from a quantitative point of view.
Course Spotlight
Mathematics 330: Statistics I
The topics in this course include random variables, both discrete and continuous; basic sampling theory, including limit theorems; and an introduction to confidence intervals.