Mathematics, B.S. to M.A. Accelerated Program
The mathematics studies accelerated bachelor's/master's program at Â鶹´«Ã½ offers outstanding mathematics studies majors the opportunity to begin an M.A. program in their senior year.
Students complete the M.A. with a full-time fifth year of graduate study at SLU after their successful completion of both the first-year requirements and their undergraduate degree and major.
For additional information, see the catalog entries for the following SLU programs:
Students wishing to apply to this ABM program should already have completed all 2000-level coursework required in mathematics for the BS in mathematics, have completed at least 75 hours at the time of application, and have completed MATHÌý3120 Introduction to Linear Algebra (3 cr). They must have a cumulative GPA of 3.00 or higher in their mathematics coursework and their overall SLU transcript, and they must have received a B or higher in both MATHÌý2660 and MATHÌý3120. To apply, students must submit a personal statement and arrange for two letters of recommendation from mathematics faculty members.
Continuation Standards
Students’ continuation in the accelerated program will be monitored by the director of graduate studies, who will also serve as their academic advisor for the graduate portion of the program. Students will meet each semester, starting in Fall of Year 4, with the graduate advisor to discuss progress.
Continuation in the ABM program requires the following cumulative GPA requirements:
- 3.0 GPA on the overall SLU transcript
- 3.00 GPA in all MATH and STAT courses
- 3.00 GPA in all courses counting towards the mathematics MA
If a student falls below the GPA requirement in any one area, they are on probation and need to bring the GPA back above 3.00 in the next semester or they will not be allowed to continue in the program.
Roadmaps are recommended semester-by-semester plans of study for programs and assume full-time enrollmentÌýunless otherwise noted. Ìý
Courses and milestones designated as critical (marked with !) must be completed in the semester listed to ensure a timely graduation. Transfer credit may change the roadmap.
This roadmap should not be used in the place of regular academic advising appointments. All students are encouraged to meet with their advisor/mentor each semester. Requirements, course availability and sequencing are subject to change.
Year One | ||
---|---|---|
Fall | Credits | |
MATHÌý1510 | Calculus I | 4 |
COREÌý1500 | Cura Personalis 1: Self in Community | 1 |
University Core and/or General Electives | 8 | |
Ìý | Credits | 13 |
Spring | ||
MATHÌý1520 | Calculus II | 4 |
Programming Course 1 | 3-4 | |
University Core and/or General Electives | 9 | |
Ìý | Credits | 16-17 |
Year Two | ||
Fall | ||
MATHÌý2530 | Calculus III | 4 |
MATHÌý2660 | Principles of Mathematics | 3 |
University Core and/or General Electives | 9 | |
Ìý | Credits | 16 |
Spring | ||
MATHÌý3120 | Introduction to Linear Algebra | 3 |
STATÌý3850 | Foundation of Statistics | 3 |
University Core and/or General Electives | 9 | |
Ìý | Credits | 15 |
Year Three | ||
Fall | ||
MATHÌý4110 | Introduction to Abstract Algebra | 3 |
Mathematics or Statistics Elective 2 | 3 | |
University Core and/or General Electives | 9 | |
Ìý | Credits | 15 |
Spring | ||
Pure Mathematics Elective 3 | 3 | |
Mathematics or Statistics Elective 2 | 3 | |
University Core and/or General Electives | 9 | |
Ìý | Credits | 15 |
Year Four | ||
Fall | ||
MATHÌý5011 | Introduction to Abstract Algebra | 3 |
MATHÌý5021 | Introduction to Analysis | 3 |
University Core and/or General Electives | 6 | |
Ìý | Credits | 12 |
Spring | ||
MATHÌý5012 or MATHÌý5015 |
Linear Algebra or Number Theory |
3 |
MATHÌý5022 or MATHÌý5023 |
Metric Spaces or Multivariable Analysis |
3 |
Core: Social Science | 3 | |
University Core and/or General Electives | 6 | |
Ìý | Credits | 15 |
Year Five | ||
Fall | ||
MATHÌý5110 | Algebraic Structures I | 3 |
MATHÌý5210 | Measure Theory | 3 |
MATHÌý5310 | Point Set Topology | 3 |
Ìý | Credits | 9 |
Spring | ||
MATHÌý5120 | Algebra II | 3 |
MATHÌý5220 or MATHÌý6230 or MATHÌý5240 |
Complex Analysis or Functional Analysis or Harmonic Analysis |
3 |
MATHÌý5320 | General Topology II | 3 |
Ìý | Credits | 9 |
Ìý | Total Credits | 135-136 |
- 1
See note below about the programming requirement.
- 2
See note below about mathematics and statistics electives.
- 3
See note below about the pure mathematics sequence requirement.
- 4
See note below about mathematics and statistics sequences.
- 5
See note below about allied electives.
Program Notes
Programming Requirement
CSCIÌý1060 Introduction to Computer Science: Scientific Programming (3 cr)ÌýorÌýCSCIÌý1300 Introduction to Object-Oriented Programming (4 cr)Ìý(with attention paid to prerequisites).
Mathematics and Statistics Elective
Any 3000- or 4000-level MATH or STAT course numbered higher thanÌýMATHÌý3120 Introduction to Linear Algebra (3 cr).
Pure Mathematics Sequence
Students can satisfy the pure mathematics sequence requirement by completing either the algebra sequence or real analysis sequence, as defined below.
Mathematics and Statistics Sequences
Students must complete a second sequence in addition to the pure mathematics sequence, chosen from the following list.
- Algebra Sequence:ÌýMATHÌý4110 Introduction to Abstract Algebra (3 cr)Ìýand eitherÌýMATHÌý4120 Linear Algebra (3 cr)ÌýorÌýMATHÌý4150 Number Theory (3 cr).
- Complex Analysis Sequence:ÌýMATHÌý4310 Introduction to Complex Variables (3 cr)Ìýand eitherÌýMATHÌý4320 Complex Variables II (3 cr)Ìýor MATH 4360 Geometric Topology (3 cr).
- Differential Equations Sequence:ÌýMATHÌý3550 Differential Equations (3 cr)Ìýand eitherÌýMATHÌý4550 Nonlinear Dynamics and Chaos (3 cr)ÌýorÌýMATHÌý4570 Partial Differential Equations (3 cr).
- Real Analysis Sequence:ÌýMATHÌý4210 Introduction to Analysis (3 cr)Ìýand one of eitherÌýMATHÌý4220 Metric Spaces (3 cr)ÌýorÌýMATHÌý4230 Multivariable Analysis (3 cr).
- Statistics Sequence:ÌýSTATÌý3850 Foundation of Statistics (3 cr)Ìýand one of:ÌýMATHÌý4800 Probability Theory (3 cr),ÌýSTATÌý4840 Time Series (3 cr), orÌýSTATÌý4870 Applied Regression (3 cr).
Allied Elective
A course in another discipline that has a strong mathematical or computational component. Appropriate courses are available in computer science, economics, physics and other science and engineering disciplines. This course cannot be used to satisfy any of the other requirements for a B.S. degree. See the course catalog for a list and description of acceptable courses.