Course Descriptions

• 1190 - Putnam Exam Seminar
• 1301 - PreCalculus
• 1307 - Calculus I for Life and Social Sciences
• 1308 - Calculus II for Life and Social Sciences
• 1310 - Mathematics for Decision Making
• 1311 - Calculus I
• 1312 - Calculus II
• 1320 - Statistical Methods
• 2303 - Math for Elementary School Teachers
• 2321 - Calculus III
• 2324 - Numerical Calculus
• 3310 - Mathematical Models in Life Sciences
• 3311 - Probabilistic Models in Life Sciences
• 3323 - Linear Algebra
• 3326 - Introduction to Abstract Mathematics
• 3334 - Probability
• 3335 - Mathematical Statistics

  This course covers the basic concepts of statistics, including samples, statistics, estimation, sampling distribution of estimators, confidence intervals, tests of hypotheses, significance, power, and simple linear regression. Additional topics may include Bayesian statistics, analysis of variance, and nonparametric methods. Spring. Prerequisite: MATH 3334.

• 3336 - Differential Equations & Linear Algebra
• 3338 - Mathematical Modeling
• 3341 - Number Theory I
• 3343 - Combinatorics I
• 3351 - Numerical Analysis I & II
• 3355 - Non-Euclidean Geometry
• 3357 - Partial Differential Equations
• 3359 - Difference Equations
• 3360 - Real Analysis I
• 3362 - Modern Algebra I
• 3366 - Differential Equations
• 3x90 - Reading and Conference
• 4324 - Linear Algebra II
• 4336 - Stochastic Processes
• 4342 - Number Theory II
• 4344 - Combinatorics II
• 4361 - Real Analysis II
• 4363 - Modern Algebra II
• 4364 - Theory of Complex Variables
• 4365 - Topology
• 4367 - Dynamical Systems
• 4391 - Special Topics
• 2094 - Major's Seminar
• 3194 - Junior Writing Workshop Seminar
• 4394 - Senior Project
• 4398/4399 - Honors Thesis