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Academic Catalog 2025-26

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Your search for courses · during 25FA · tagged with MATH Applied Mathematics · returned 3 results

  • MATH 240 Probability 6 credits

    Introduction to probability and its applications. Topics include discrete probability, random variables, independence, joint and conditional distributions, expectation, limit laws and properties of common probability distributions.

    • Fall 2025
    • FSR, Formal or Statistical Reasoning
    • Student has completed any of the following course(s): MATH 120 or MATH 211 or greater with a grade of C- or better or received a Carleton MATH 211 or better Requisite Equivalency or equivalent.

    • CL: 200 level ENTS Quantitative Methods MATH Electives SDSC Math Stats Elective STAT Core MATH Applied Mathematics
    • MATH  240.01 Fall 2025

    • Faculty:Katie St. Clair 🏫 πŸ‘€
    • Size:30
    • M, WCMC 306 8:30am-9:40am
    • FCMC 306 8:30am-9:30am
    • MATH  240.02 Fall 2025

    • Faculty:Josh Davis 🏫 πŸ‘€
    • Size:30
    • M, WCMC 301 9:50am-11:00am
    • FCMC 301 9:40am-10:40am
  • MATH 241 Ordinary Differential Equations 6 credits

    Ordinary differential equations are a fundamental language used by mathematicians, scientists, and engineers to describe processes involving continuous change. In this course we develop ordinary differential equations as models of real world phenomena and explore the mathematical ideas that arise within these models. Topics include separation of variables; phase portraits; equilibria and their stability; non-dimensionalization; bifurcation analysis; and modeling of physical, biological, chemical, and social processes.

    • Fall 2025
    • FSR, Formal or Statistical Reasoning
    • Student must have completed any of the following course(s): MATH 134 or MATH 232 AND MATH 120 or MATH 211 with a grade of C- or better or equivalents.

    • CL: 200 level MATH Electives PHYS Addl Recommended MATH Applied Mathematics
    • MATH  241.01 Fall 2025

    • Faculty:Kate Meyer 🏫 πŸ‘€
    • Size:25
    • M, WCMC 210 11:10am-12:20pm
    • FCMC 210 12:00pm-1:00pm
  • STAT 340 Bayesian Statistics 6 credits

    The Bayesian approach to statistics provides a powerful framework for incorporating prior knowledge into statistical analyses, updating this knowledge with data, and quantifying uncertainty in results. This course serves as a comprehensive introduction to Bayesian statistical inference and modeling, an alternative to the frequentist approach to statistics covered in previous classes. Topics include: Bayes’ Theorem; prior and posterior distributions; Bayesian regression; hierarchical models; and model adequacy and posterior predictive checks. Computational techniques will also be covered, including Markov Chain Monte Carlo methods, and modern Bayesian modeling packages in R.

    • Fall 2025
    • FSR, Formal or Statistical Reasoning QRE, Quantitative Reasoning
    • Student has completed any of the following course(s): STAT 230 and STAT 250 with a grade of C- or better.

    • CL: 300 level MATH Electives SDSC Math Stats Elective STAT Elective MATH Applied Mathematics
    • STAT  340.01 Fall 2025

    • Faculty:Amanda Luby 🏫 πŸ‘€
    • Size:20
    • M, WCMC 306 11:10am-12:20pm
    • FCMC 306 12:00pm-1:00pm

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2025–26 Academic Catalog

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Registrar: Theresa Rodriguez
Email: registrar@carleton.edu
Phone: 507-222-4094
Academic Catalog 2025-26 pages maintained by Maria Reverman
This page was last updated on 28 January 2026
Carleton

One North College StNorthfield, MN 55057USA

507-222-4000

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