Mathematics (B.S.)
Required course work includes the university requirements (see regulation J-3) and:
| Code | Title | Hours |
|---|---|---|
| MATH 170 | Calculus I | 4 |
| MATH 175 | Calculus II | 4 |
| MATH 275 | Calculus III | 3 |
| MATH 310 | Ordinary Differential Equations | 3 |
| MATH 330 | Linear Algebra | 3 |
| Options | ||
| Select one of the following options: | 36-54 | |
| Total Hours | 53-71 | |
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.
| Code | Title | Hours |
|---|---|---|
| Math Courses | ||
| MATH 176 | Discrete Mathematics | 3 |
| MATH 215 | Proof via Number Theory | 3 |
| MATH 310 | Ordinary Differential Equations | 3 |
| MATH 461 | Abstract Algebra I | 3 |
| MATH 471 | Introduction to Analysis I | 3 |
| Select one of the following: | 3 | |
| Advanced Linear Algebra | ||
| Mathematical Statistics | ||
| Stochastic Models | ||
| Abstract Algebra II | ||
| Introduction to Analysis II | ||
| Combinatorics | ||
| Select four math courses above 310 | 12 | |
| Supporting Courses | ||
| STAT 301 | Probability and Statistics | 3 |
| CS 112 | Computational Thinking and Problem Solving | 3 |
| or CS 120 | Computer Science I | |
| Total Hours | 36 | |
Courses to total 120 credits for this degree
B. 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.
| Code | Title | Hours |
|---|---|---|
| Math Courses | ||
| MATH 176 | Discrete Mathematics | 3 |
| MATH 215 | Proof via Number Theory | 3 |
| MATH 310 | Ordinary Differential Equations | 3 |
| MATH 385 | Theory of Computation | 3 |
| MATH 395 | Analysis of Algorithms | 3 |
| MATH 415 | Cryptography | 3 |
| MATH 428 | Numerical Methods | 3 |
| or MATH 432 | Numerical Linear Algebra | |
| MATH 452 | Mathematical Statistics | 3 |
| or STAT 301 | Probability and Statistics | |
| Select two additional courses from the following: | 6 | |
| Discrete Mathematics II | ||
| Discrete Optimization | ||
| Advanced Linear Algebra | ||
| Numerical Linear Algebra | ||
| Probability Theory | ||
| Mathematical Statistics | ||
| Abstract Algebra I | ||
| Abstract Algebra II | ||
| Combinatorics | ||
| Supporting Courses | ||
| CS 120 | Computer Science I | 4 |
| CS 121 | Computer Science II | 3 |
| Total Hours | 37 | |
Courses to total 120 credits for this degree
C. Applied - Modeling and Data Science Option
The emphasis is on the mathematics used to model phenomena in engineering, science, business and economics. With a second major in one of these disciplines, this provides ideal preparation for graduate school.
| Code | Title | Hours |
|---|---|---|
| Math Courses | ||
| MATH 176 | Discrete Mathematics | 3 |
| MATH 183 | Introduction to Data Science in Python | 3 |
| MATH 310 | Ordinary Differential Equations | 3 |
| MATH 428 | Numerical Methods | 3 |
| or MATH 432 | Numerical Linear Algebra | |
| MATH 451 | Probability Theory | 3 |
| MATH 483 | Foundations of Machine Learning | 3 |
| or MATH 438 | Mathematical Modeling | |
| STAT 301 | Probability and Statistics | 3 |
| or MATH 452 | Mathematical Statistics | |
| Select four additional courses from the following: | 12 | |
| Database Systems | ||
| Theory of Computation | ||
| Analysis of Algorithms | ||
| Parallel Programming | ||
| Computational Biology: Sequence Analysis | ||
| Data Communication Systems | ||
| Artificial Intelligence | ||
| Data Science | ||
| Mathematical Physics | ||
| Discrete Mathematics II | ||
| Complex Variables | ||
| Numerical Methods | ||
| Numerical Linear Algebra | ||
| Mathematical Biology | ||
| Mathematical Modeling | ||
| Mathematical Statistics | ||
| Stochastic Models | ||
| Combinatorics | ||
| Partial Differential Equations | ||
| Foundations of Machine Learning | ||
| Database Design | ||
| Data Management for Big Data | ||
| Dynamic Modeling of Engineering Systems | ||
| Social Data Analysis | ||
| Statistical Analysis | ||
| Quantitative Electives | ||
| Select 6 credits of advisor-approved quantitative electives in Science, Engineering, Business, Economics, etc. These electives can be drawn from the above list, as long as they are not used to fulfill the elective requirement. | 6 | |
| Total Hours | 39 | |
Courses to total 120 credits for this degree
D. Applied - Mathematical Biology Option
This option offers training across Mathematics and Biology and provides the background to pursue a career in technical industries and to obtain graduate degrees in Biomathematics, Biostatistics, and Bioinformatics.
| Code | Title | Hours |
|---|---|---|
| Math Courses | ||
| MATH 437 | Mathematical Biology | 3 |
| MATH 451 | Probability Theory | 3 |
| MATH 453 | Stochastic Models | 3 |
| MATH 480 | Partial Differential Equations | 3 |
| Select one course from the following: | 3 | |
| Numerical Methods | ||
| Numerical Linear Algebra | ||
| Select three courses from the following: | 9 | |
| Complex Variables | ||
| Advanced Linear Algebra | ||
| Mathematical Modeling | ||
| Mathematical Statistics | ||
| Introduction to Analysis I | ||
| Introduction to Analysis II | ||
| Foundations of Machine Learning | ||
| Biology Courses | ||
| Select 9 credits of advisor-approved electives in the biological sciences | 9 | |
| Supporting Courses | ||
| Select one from the following | 3 | |
| Computer Science I | ||
| Introduction to Data Science in Python | ||
| Introduction to SAS/R Programming | ||
| SAS Programming | ||
| R Programming | ||
| Total Hours | 36 | |
Courses to total 120 credits for this degree
General Option
| Fall Term 1 | Hours | |
|---|---|---|
| ENGL 101 | Writing and Rhetoric I | 3 |
| MATH 143 | College Algebra | 3 |
| COMM 101 | Fundamentals of Oral Communication | 3 |
| Scientific Ways of Knowing Course | 4 | |
| American Diversity Course | 3 | |
| Hours | 16 | |
| Spring Term 1 | ||
| ENGL 102 | Writing and Rhetoric II | 3 |
| MATH 144 | Analytic Trigonometry | 1 |
| MATH 170 | Calculus I | 4 |
| Humanistic and Artistic Ways of Knowing Course | 3 | |
| CS 112 OR CS 120 | 3 | |
| Hours | 14 | |
| Fall Term 2 | ||
| MATH 175 | Calculus II | 4 |
| MATH 176 | Discrete Mathematics | 3 |
| International Course | 3 | |
| Social and Behavioral Ways of Knowing Course | 3 | |
| Elective Course | 2 | |
| Hours | 15 | |
| Spring Term 2 | ||
| MATH 215 | Proof via Number Theory | 3 |
| MATH 275 | Calculus III | 3 |
| MATH 330 | Linear Algebra | 3 |
| Social and Behavioral Ways of Knowing Course | 3 | |
| Scientific Ways of Knowing Course | 4 | |
| Hours | 16 | |
| Fall Term 3 | ||
| STAT 301 | Probability and Statistics | 3 |
| MATH 310 | Ordinary Differential Equations | 3 |
| MATH 461 | Abstract Algebra I | 3 |
| Elective Course | 3 | |
| Elective Course | 3 | |
| Hours | 15 | |
| Spring Term 3 | ||
| Mathematics above 310, Major Elective Course | 3 | |
| Humanistic and Artistic Ways of Knowing Course | 3 | |
| Elective Course | 3 | |
| Elective Course | 3 | |
| MATH 430 OR MATH 452 OR MATH 453 OR MATH 462 OR MATH 472 OR MATH 476 | 3 | |
| Hours | 15 | |
| Fall Term 4 | ||
| MATH 415 | Cryptography | 3 |
| MATH 471 | Introduction to Analysis I | 3 |
| Mathematics above 310, Major Elective Course | 3 | |
| Elective Course | 3 | |
| Elective Course | 3 | |
| Hours | 15 | |
| Spring Term 4 | ||
| Mathematics above 310, Major Elective Course | 3 | |
| Mathematics above 310, Major Elective Course | 3 | |
| Elective Course | 3 | |
| Elective Course | 3 | |
| Elective Course | 3 | |
| Hours | 15 | |
| Total Hours | 121 | |
Applied - Computation Option
| Fall Term 1 | Hours | |
|---|---|---|
| ENGL 101 | Writing and Rhetoric I | 3 |
| MATH 143 | College Algebra | 3 |
| American Diversity Course | 3 | |
| Oral Communication Course | 2 | |
| Scientific Ways of Knowing Course | 4 | |
| Hours | 15 | |
| Spring Term 1 | ||
| CS 120 | Computer Science I | 4 |
| ENGL 102 | Writing and Rhetoric II | 3 |
| MATH 144 | Analytic Trigonometry | 1 |
| MATH 170 | Calculus I | 4 |
| Humanistic and Artistic Ways of Knowing Course | 3 | |
| Hours | 15 | |
| Fall Term 2 | ||
| CS 121 | Computer Science II | 3 |
| MATH 175 | Calculus II | 4 |
| MATH 176 | Discrete Mathematics | 3 |
| International Course | 3 | |
| Elective Course | 3 | |
| Hours | 16 | |
| Spring Term 2 | ||
| MATH 215 | Proof via Number Theory | 3 |
| MATH 275 | Calculus III | 3 |
| MATH 330 | Linear Algebra | 3 |
| Scientific Ways of Knowing Course | 4 | |
| Social and Behavioral Ways of Knowing Course | 3 | |
| Hours | 16 | |
| Fall Term 3 | ||
| MATH 310 | Ordinary Differential Equations | 3 |
| MATH 385 | Theory of Computation | 3 |
| Elective Course | 3 | |
| Social and Behavioral Ways of Knowing Course | 3 | |
| MATH 452 OR STAT 301 | 3 | |
| Hours | 15 | |
| Spring Term 3 | ||
| MATH 395 | Analysis of Algorithms | 3 |
| Humanistic and Artistic Ways of Knowing Course | 3 | |
| Elective Course | 3 | |
| Elective Course | 3 | |
| MATH 376 OR MATH 426 OR MATH 430 OR MATH 432 OR MATH 451 OR MATH 452 OR MATH 461 OR MATH 462 OR MATH 476 | 3 | |
| Hours | 15 | |
| Fall Term 4 | ||
| MATH 415 | Cryptography | 3 |
| Elective Course | 3 | |
| Elective Course | 3 | |
| Elective Course | 3 | |
| MATH 376 OR MATH 426 OR MATH 432 OR MATH 451 OR MATH 452 OR MATH 461 OR MATH 462 OR MATH 476 | 3 | |
| Hours | 15 | |
| Spring Term 4 | ||
| Elective Course | 3 | |
| Elective Course | 3 | |
| Elective Course | 3 | |
| 1 credit Elective Course | 1 | |
| MATH 428 OR MATH 432 | 3 | |
| Hours | 13 | |
| Total Hours | 120 | |
Applied - Modeling and Data Science Option
| Fall Term 1 | Hours | |
|---|---|---|
| ENGL 101 | Writing and Rhetoric I | 3 |
| MATH 143 | College Algebra | 3 |
| American Diversity Course | 3 | |
| Oral Communication Course | 2 | |
| Scientific Ways of Knowing Course | 4 | |
| Hours | 15 | |
| Spring Term 1 | ||
| ENGL 102 | Writing and Rhetoric II | 3 |
| MATH 144 | Analytic Trigonometry | 1 |
| MATH 170 | Calculus I | 4 |
| Humanistic and Artistic Ways of Knowing Course | 3 | |
| Scientific Ways of Knowing Course | 4 | |
| Hours | 15 | |
| Fall Term 2 | ||
| MATH 175 | Calculus II | 4 |
| MATH 176 | Discrete Mathematics | 3 |
| Social and Behavioral Ways of Knowing Course | 3 | |
| International Course | 3 | |
| Elective Course | 3 | |
| Hours | 16 | |
| Spring Term 2 | ||
| MATH 183 | Introduction to Data Science in Python | 3 |
| MATH 275 | Calculus III | 3 |
| MATH 330 | Linear Algebra | 3 |
| Elective Course | 3 | |
| Social and Behavioral Ways of Knowing Course | 3 | |
| Hours | 15 | |
| Fall Term 3 | ||
| MATH 310 | Ordinary Differential Equations | 3 |
| MATH 451 | Probability Theory | 3 |
| Elective Course | 3 | |
| Elective Course | 3 | |
| Mathematics, Major Elective Course | 3 | |
| Hours | 15 | |
| Spring Term 3 | ||
| MATH elec, or Senior Exp., Major Elective Course | 3 | |
| Modeling, Major Elective Course | 3 | |
| Humanistic and Artistic Ways of Knowing Course | 3 | |
| Elective Course | 3 | |
| MATH 452 OR STAT 301 | 3 | |
| Hours | 15 | |
| Fall Term 4 | ||
| Modeling, Major Elective Course | 3 | |
| MATH elective or Senior Exp., Major Elective Course | 3 | |
| Mathematics, Major Elective Course | 3 | |
| Elective Course | 3 | |
| MATH 438 OR MATH 483 | 3 | |
| Hours | 15 | |
| Spring Term 4 | ||
| Mathematics, Major Elective Course | 3 | |
| Mathematics, Major Elective Course | 3 | |
| Elective Course | 3 | |
| Elective Course | 2 | |
| MATH 428 OR MATH 432 | 3 | |
| Hours | 14 | |
| Total Hours | 120 | |
Applied - Mathematical Biology Option
| Fall Term 1 | Hours | |
|---|---|---|
| ENGL 101 | Writing and Rhetoric I | 3 |
| MATH 143 | College Algebra | 3 |
| BIOL 114 | Organisms and Environments | 4 |
| COMM 101 | Fundamentals of Oral Communication | 3 |
| American Diversity Course | 3 | |
| Hours | 16 | |
| Spring Term 1 | ||
| ENGL 102 | Writing and Rhetoric II | 3 |
| MATH 144 | Analytic Trigonometry | 1 |
| MATH 170 | Calculus I | 4 |
| CHEM 111 | General Chemistry I | 3 |
| CHEM 111L | General Chemistry I Laboratory | 1 |
| Humanistic and Artistic Ways of Knowing Course | 3 | |
| Hours | 15 | |
| Fall Term 2 | ||
| MATH 175 | Calculus II | 4 |
| BIOL 115 | Cells and the Evolution of Life | 3 |
| BIOL 115L | Cells and the Evolution of Life Laboratory | 1 |
| Social and Behavioral Ways of Knowing Course | 3 | |
| International Course | 3 | |
| 1 credit Elective Course | 1 | |
| Hours | 15 | |
| Spring Term 2 | ||
| MATH 275 | Calculus III | 3 |
| MATH 330 | Linear Algebra | 3 |
| Humanistic and Artistic Ways of Knowing Course | 3 | |
| UPDV Biology, Major Elective Course | 3 | |
| STAT 251 OR STAT 301 | 3 | |
| Hours | 15 | |
| Fall Term 3 | ||
| BIOL 310 | Genetics | 3 |
| MATH 451 | Probability Theory | 3 |
| Elective Course | 3 | |
| Elective Course | 3 | |
| MATH 310 OR MATH 453 OR STAT 431 | 3 | |
| Hours | 15 | |
| Spring Term 3 | ||
| MATH 437 | Mathematical Biology | 3 |
| MATH 452 | Mathematical Statistics | 3 |
| UPDV Biology, Major Elective Course | 3 | |
| Social and Behavioral Ways of Knowing Course | 3 | |
| Elective Course | 3 | |
| Hours | 15 | |
| Fall Term 4 | ||
| BIOL 456 | Computer Skills for Biologists | 3 |
| MATH 415 | Cryptography | 3 |
| UPDV Biology, Major Elective Course | 3 | |
| Elective Course | 3 | |
| MATH 428 OR MATH 430 OR MATH 480 | 3 | |
| Hours | 15 | |
| Spring Term 4 | ||
| UPDV Biology, Elective Course | 3 | |
| Elective Course | 3 | |
| Elective Course | 3 | |
| MATH 310 OR MATH 453 OR STAT 431 | 3 | |
| MATH 428 OR MATH 430 OR MATH 480 | 3 | |
| Hours | 15 | |
| Total Hours | 121 | |
The degree map is a guide for the timely completion of your curricular requirements. Your academic advisor or department may be contacted for assistance in interpreting this map. This map is not reflective of your academic history or transcript and it is not official notification of completion of degree or certificate requirements. Please contact the Registrar's Office regarding your official degree/certificate completion status.
- Students should be able to think critically, apply problem solving strategies, and be able to construct and defend mathematical proofs.
- Students should be able to use mathematical structures and the language of mathematics to formulate models for real-world problems.
- Students should be able to effectively communicate their work and should gain experience working in collaborative settings.
- Students should be able to interpret and extract relevant information from data using appropriate modeling techniques.