Mathematics Undergraduate Curricular Requirements
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Mathematics (B.S.)
Required course work includes the university requirements (see regulation J-3) and:
Basic Courses:
Analytic Geometry and Calculus I (4 cr) |
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Analytic Geometry and Calculus II (4 cr) |
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Analytic Geometry and Calculus III (3 cr) |
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Linear Algebra or |
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Advanced Linear Algebra (3cr) |
And one of the following options:
A. General Option
This is the traditional curriculum in Mathematics. It is more mathematically rigorous than the other options. It is especially good for secondary education majors and students intending to go to graduate school in Mathematics or other sciences.
Math Courses:
Introduction to Higher Mathematics (3 cr) |
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Ordinary Differential Equations (3 cr) |
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Abstract Algebra (3 cr) |
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Abstract Algebra or |
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Introduction to Analysis 2 (3 cr) |
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Introduction to Analysis 1 (3 cr) |
Three credits in Math electives numbered above 310.
Six credits chosen from Math 385, ECE 455, Stat 401, or any Math course numbered above 400.
Supporting Courses:
Engineering Physics I (3 cr) |
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Engineering Physics II (3 cr) |
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Statistical Methods or |
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Probability and Statistics (3 cr) |
B. Applied - Statistics Option
The emphasis is on the design and analysis of experiments. With a major or minor in another department this is an excellent preparation for work in industry or for graduate school in Statistics.
Math Courses:
Probability Theory (3 cr) |
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Mathematical Statistics (3 cr) |
At least two courses from the following (6 cr):
Analysis of Algorithms (3 cr) |
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Discrete Optimization (3 cr) |
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Numerical Methods (3 cr) |
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Numerical Linear Algebra (3 cr) |
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Introduction to Analysis 1 (3 cr) |
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Introduction to Analysis 2 (3 cr) |
Supporting Courses:
Introduction to Problem Solving and Programming or |
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Computer Science I (3-4 cr ) |
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Statistical Analysis (3 cr) |
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Beginning SAS Programming (1 cr) |
One course selected from the following (3-4 cr):
Statistical Methods (3 cr) |
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Probability and Statistics (recommended) (3 cr) |
At least two courses from the following (6 cr):
Quantitative Economics and Forecasting (3 cr) |
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Stochastic Models (3 cr) |
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Sample Survey Methods (3 cr) |
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Experimental Design (3 cr) |
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Regression (3 cr) |
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Nonparametric Statistics (3 cr) |
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Multivariate Analysis (3 cr) |
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Statistical Ecology (3 cr) |
Approved electives in fields where statistics is applied (not to be in Statistics (Stat) courses) (6 cr)
C. Applied - Computation Option
The emphasis is on the mathematics related to computer science and technology. With a major or minor in computer sciences this is a good preparation for work in the computer industry.
Math courses:
Discrete Mathematics (3 cr) |
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Theory of Computation (3 cr) |
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Analysis of Algorithms (3 cr) |
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Numerical Methods (3 cr) |
Three courses from the following (9 cr):
Cryptography (3 cr) |
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Discrete Optimization (3 cr) |
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Advanced Linear Algebra (3 cr) |
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Numerical Linear Algebra (3 cr) |
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Probability Theory (3 cr) |
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Abstract Algebra (3 cr) |
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Abstract Algebra (3 cr) |
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Combinatorics (3 cr) |
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Partial Differential Equations (3 cr) |
Two courses from the following (6 cr):
Ordinary Differential Equations (3 cr) |
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Linear Optimization (3 cr) |
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Discrete Mathematics II (3 cr) |
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Probability and Statistics (3 cr) |
Any Math course numbered 401-499, Stat 401, or ECE 455 (3 cr)
Supporting courses:
Computer Science I (4 cr) |
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Computer Science II (4 cr) |
D. Applied Scientific Modeling Option
The emphasis is on the mathematics used to model phenomena in the sciences. With a second major in a science this provides ideal preparation for graduate school.
Math courses:
Ordinary Differential Equations (3 cr) |
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Probability Theory (3 cr) |
One of the following (3 cr):
Information and Coding Theory (3 cr) |
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Mathematical Biology (3 cr) |
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Ecological Modeling (3 cr) |
Five additional courses from the following (15 cr):
Signals and Systems I (3 cr) |
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Signals and Systems II (3 cr) |
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Information and Coding Theory (3 cr) |
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Linear Optimization (3 cr) |
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Mathematical Physics (3 cr) |
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Discrete Mathematics II (3 cr) |
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Cryptography (3 cr) |
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Complex Variables (3 cr) |
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Discrete Optimization (3 cr) |
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Numerical Methods (3 cr) |
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Numerical Linear Algebra (3 cr) |
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Mathematical Biology (3 cr) |
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Mathematical Statistics (3 cr) |
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Stochastic Models (3 cr) |
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Introduction to Analysis 1 (3 cr) |
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Introduction to Analysis 2 (3 cr) |
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Combinatorics (3 cr) |
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Partial Differential Equations (3 cr) |
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Probability and Statistics (3 cr) |
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Ecological Modeling (3 cr) |
Supporting courses:
Introduction to Problem Solving and Programming or |
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Computer Science I (3-4 cr) |
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Probability and Statistics or |
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Mathematical Statistics (3 cr) |
Two courses at the 300 level or above in one area of science, engineering, or other quantitative area.
E. Applied - Actuarial Science and Finance Option
This curriculum provides the background to become an actuary and work in the insurance industry, or to work in finance.
Math courses:
Ordinary Differential Equations (3 cr) |
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Probability Theory (3 cr) |
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Mathematical Statistics (3 cr) |
In addition to the above courses, an additional three math courses numbered above 400, excluding Math 513-519 (9 cr)
Supporting courses:
Introduction to Financial Accounting (3 cr) |
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Introduction to Managerial Accounting (3 cr) |
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Financial Management (3 cr) |
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Introduction to Problem Solving and Programming or |
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Computer Science I (3-4 cr) |
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Principles of Economics (3 cr) |
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Principles of Economics (3 cr) |
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Statistical Analysis (3 cr) |
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Beginning SAS Programming or |
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Spreadsheet Modeling (1 cr) |
At least two course selected from the following (6 cr):
Intermediate Financial Management (3 cr) |
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Security Analysis (3 cr) |
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Portfolio Management (3 cr) |
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Derivatives and Financial Engineering (3 cr) |
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Introduction to Market Trading (3 cr) |
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International Finance (3 cr) |
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Intermediate Macroeconomic Analysis (3 cr) |
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Intermediate Microeconomic Analysis (3 cr) |
Both of the following:
Insurance (3 cr) |
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Applied Actuarial Science (1 cr) |
One course selected from the following (3-4 cr):
Probability and Statistics (recommended) (3 cr) |
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Statistical Methods (3 cr) |
One course selected from the following (3 cr):
Quantitative Economics and Forecasting (3 cr) |
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Econometrics (3 cr) |
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Regression (3 cr) |
F. Applied - Operations Research Option
The emphasis is on the mathematics used in the modeling and analysis of problems from business and industry.
Math courses:
Linear Optimization (3 cr) |
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Discrete Optimization (3 cr) |
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Probability Theory (3 cr) |
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Stochastic Models (3 cr) |
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Combinatorics (3 cr) |
At least one course from the following (3 cr):
Ordinary Differential Equations (3 cr) |
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Discrete Mathematics II (3 cr) |
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Mathematical Statistics (3 cr) |
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Statistical Analysis (3 cr) |
Any other 400-level math course
Supporting courses:
Introduction to Managerial Accounting (3 cr) |
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Introduction to Operations Management (3 cr) |
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Introduction to Problem Solving and Programming or |
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Computer Science I (3-4 cr) |
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Probability and Statistics (3 cr) |
Four of the following courses (two must be above 400) (12 cr):
Management Information Systems (3 cr) |
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Systems Analysis and Design (3 cr) |
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Project Management (3 cr) |
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Systems and Simulation (3 cr) |
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Quality Management (3 cr) |
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Operations Planning and Scheduling (3 cr) |
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Econometrics (3 cr) |