Bard College at Simon's Rock: the Early College
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Quantitative Studies Curriculum

Apply the study of quantitative studies to a wide variety of phenomena across disciplines.

A concentration in Quantitative Studies 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. This concentration helps prepare graduates for future training or careers in mathematics, computer science, actuarial sciences, education, medicine, law, and economics, among others.

The minimum requirements for the concentration are:

  • one course in statistics (either MATH 110 or MATH 330)
  • 12 credits of intermediate courses,
  • one year-long sequence in mathematics at the 300-level
  • two courses at the 300-level or above in the area of application

Twenty-eight credits overall is required, except that students with advanced placement may satisfy the concentration requirements with 24-27 credits (and fewer than 12 credits of intermediate courses). Intermediate courses which the student places out of do not count toward the overall concentration credit requirement.



  • Introduction to Statistics (MATH 110) - optional for Statistics track, required for Differential Equations track


12 credits from:

  • Calculus I and II (MATH 210 & 211)
  • Linear Algebra and Vector Calculus (MATH 220 & 221)
  • Discrete Mathematics (MATH 252)


At least eight credits in the area of application and one of the two year-long math sequences listed in the Tracks section. Each of the math sequences will incorporate training in methodology. In addition, the following courses are usually offered at least once every four years. Other courses are offered when there is sufficient student interest.

  • Complex Analysis (MATH 310)
  • Analysis I and II (MATH 312 & 313)
  • Modern Algebra I and II (MATH 320 & 321)
  • Topology I and II (MATH 354 & 355)
  • Machine Learning (MATH 370)


Either Statistics (MATH 330, 331; MATH 331 includes the methodology of statistical inference) or Differential Equations (MATH 364, 365; both courses include the methodology of mathematical modeling).


In addition to the courses named in the Tracks section, any one of the following courses is useful for developing one's skills in axiomatics and formal proof writing; a methodology course in the area of application is also beneficial.

  • Analysis I (MATH 312)
  • Modern Algebra I (MATH 320)
  • Topology I (MATH 354)



  • On-campus internship (summer)
  • NSF-funded Research Experiences for Undergraduates (REUs) at many US universities


“Music of the Mind: A Study of Musical Perception and Meaning”

“Mechanics Problems in Billiards”

“Un–Civil War: the Design and Implementation of a Network-Based Distributed Simulation”

“ftTK: A common Structure for User Interface Elements in Microsoft Windows, X Windows, and Mac OS"

“Does Gender Play a Role in Science, Technology, Engineering, and Mathematics Education”

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