The Mathematics major consists of prescriptive common courses, prescriptive concentration courses, and elective courses. The Data Science concentration emphasizes coursework designed to give the student sound fundamental skills in statistical and computing concepts relating to the quantitative analysis of data (39 hours).
The Mathematics major requires completion of the following common courses with a “C” or better:
| Course | Title | Credits |
|---|---|---|
| MS 125 | Calculus I | 4 |
| MS 126 | Calculus II | 4 |
| MS 227 | Calculus III | 4 |
| MS 300 | Introduction to Advanced Mathematics (WI) | 3 |
| MS 344 | Differential Equations | 3 |
| MS 352 | Linear Algebra | 3 |
| MS 415 | Advanced Calculus I (WI) | 3 |
| MS 441 | Abstract Algebra I (WI) | 3 |
The Data Science concentration requires completion of the following concentration courses with a “C” or better:
| Course | Title | Credits |
|---|---|---|
| MS 302 | Applied Probability and Statistics | 3 |
| MS 444 | Applied Statistical Methods | 3 |
This concentration also requires two elective courses selected from the departmental list of approved mathematics electives;
- At least one MS course numbered 300 or higher1
- At least one MS course numbered 400 or higher
| 1 | Excludes MS 322 Selected Survey of Secondary School Mathematics (3), MS 331 Peer Educator (1), and MS 332 Peer Educator (2). |
In addition to the common, concentration, and elective courses, this concentration requires the following support courses:
| Course | Title | Credits |
|---|---|---|
| PHS 221 | Physics for Scientists and Engineers I w/Lab | 4 |
| CS 230 | Fundamentals of Computing 2 | 3 |
| CS 306 | Introduction to Data Science 2 | 3 |
| CS 445 | Predictive Analysis 2 | 3 |
| CS 480 | Special Topics in Data Science 2 | 3 |
| 2 | Grade of C or better is required for these Computer Science (CS) courses. |
A minor is not required for students majoring in Mathematics.
In addition to courses noted below, candidates for graduation must successfully complete all JSU Academic Regulations. More information about general education requirements can be found in the Summary of Degrees/Requirements section of the catalog.
| Freshman | ||
|---|---|---|
| Fall | Hours | |
| EH Composition sequence | 3 | |
| MS 125 | Calculus I | 4 |
| History | 3 | |
| CS 230 | Fundamentals of Computing 2 | 3 |
| SSC 101 | First Year Experience | 0 |
| Hours | 13 | |
| Spring | ||
| EH Composition sequence | 3 | |
| Fine Arts | 3 | |
| History/Social/Behavioral Science 1 | 3 | |
| Social/Behavioral Science | 3 | |
| MS 126 | Calculus II | 4 |
| Hours | 16 | |
| Sophomore | ||
| Fall | ||
| EH 141 | Speech | 3 |
| Literature | 3 | |
| PHS 221 | Physics for Scientists and Engineers I w/Lab | 4 |
| MS 227 | Calculus III | 4 |
| Hours | 14 | |
| Spring | ||
| Humanities & Fine Arts 1 | 3 | |
| Natural Science | 4 | |
| Social/Behavioral Science | 3 | |
| MS 300 | Introduction to Advanced Mathematics (WI) | 3 |
| MS 352 | Linear Algebra | 3 |
| Hours | 16 | |
| Junior | ||
| Fall | ||
| CS 306 | Introduction to Data Science 2 | 3 |
| MS 344 | Differential Equations | 3 |
| General Electives | 10 | |
| Hours | 16 | |
| Spring | ||
| MS 441 | Abstract Algebra I (WI) | 3 |
| MS 444 | Applied Statistical Methods | 3 |
| MS 300+ Elective | 3 | |
| General Electives | 6 | |
| Hours | 15 | |
| Senior | ||
| Fall | ||
| CS 445 | Predictive Analysis 2 | 3 |
| MS 302 | Applied Probability and Statistics | 3 |
| MS 415 | Advanced Calculus I (WI) | 3 |
| General Electives | 6 | |
| Hours | 15 | |
| Spring | ||
| CS 480 | Special Topics in Data Science 2 | 3 |
| MS 400+ Elective | 3 | |
| General Electives | 9 | |
| Hours | 15 | |
| Total Hours | 120 | |
| 1 | Either a history sequence or a literature sequence is required. |
| 2 | Grade of C or better is required for these Computer Science (CS) courses. |