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Office: Knott Hall, Room 306
Telephone: 410‑617‑2328
Fax: 410‑617‑2803
Website: www.loyola.edu/academics/mathematics-statistics

Chair: William Ethan Duckworth, Associate Professor

Professors: John C. Hennessey (emeritus); Michael P. Knapp; Christopher H. Morrell (emeritus); Jiyuan Tao; Anne L. Young (emerita)
Associate Professors: Prince Chidyagwai; Timothy B.P. Clark; William Ethan Duckworth; Lisa A. Oberbroeckling; William D. Reddy (emeritus); Dipa Sarkar Dey (emerita)
Assistant Professors: Richard E. Auer; Bu Hyoung Lee
Lecturers: Neeta Deshpande; Kevin Drummey; Giselle Pile; Amit Yavantikar
Affiliate Faculty: Kelsey Bardoff; Richard A. Brown; Ilya Kerzhner; Tamala Martin; Michael F. Schneider; Clarke Tankersley; Leanne Voos; Stacey E. Wagaman
 

In keeping with the mission of Loyola University Maryland, the Department of Mathematics and Statistics strives for excellence in education. The department offers two majors: one in mathematics and the other in statistics. The department's goal is to open students' minds to the power, beauty, and utility of mathematics and statistics and to develop their conceptual understanding, problem solving ability, and analytical thinking skills. The department's faculty is strongly committed to undergraduate teaching and to giving mathematics and statistics majors a solid and broad-based foundation for a variety of careers, as well as for graduate study. Faculty members conduct research in their fields of specialty and also keep abreast of curricular reform and creative uses of technology.

A double major requires the student to complete the requirements of each major. Students cannot double major in mathematics and statistics. Interdisciplinary majors allow students to combine interests in two different disciplines. An interdisciplinary major may be designed with the assistance of the student's academic advisor.

Learning Aims

• Students will be able to compute accurately using algebra, calculus, or higher-level mathematics.
• Students will be able to write proofs of theorems.
• Students will be able to interpret data and data summaries using statistical methods.
• Students will be able to write computer programs or run computer packages to perform quantitative tasks.

Programs

• Mathematics, BS
• Statistics, BS

• Interdisciplinary Major in Mathematics, Differential Equations/Mathematical Modeling Track
• Interdisciplinary Major in Mathematics, Discrete/Algorithmic Track
• Interdisciplinary Major in Statistics

• Mathematics Minor
• Statistics Minor

Courses

• MA 005 - Precalculus Lab
• MA 103 - Mathematics for Elementary Teachers: Algebraic
• MA 104 - Mathematics for Elementary Teachers: Geometric
• MA 109 - Precalculus
• MA 114 - Mathematics of Sustainability
• MA 115 - Introduction to Combinatorics
• MA 116 - Topics in Modern Math: Ciphers and Codes
• MA 117 - Mathematics, Numbers and the Real World
• MA 118 - History of Mathematics
• MA 119 - Special Topics in Modern Math
• MA 151 - Applied Calculus
• MA 200 - Opportunities in STEM
• MA 251 - Calculus I
• MA 252 - Calculus II
• MA 295 - Discrete Structures
• MA 301 - Introduction to Linear Algebra
• MA 302 - Programming in Mathematics
• MA 304 - Ordinary Differential Equations
• MA 351 - Calculus III
• MA 395 - Discrete Methods
• MA 421 - Analysis I
• MA 422 - Analysis II
• MA 424 - Complex Analysis
• MA 427 - Numerical Analysis
• MA 428 - Computational Mathematics
• MA 431 - Geometry
• MA 437 - Combinatorics
• MA 441 - Ring Theory
• MA 442 - Group Theory
• MA 443 - Polynomial Algebra
• MA 445 - Advanced Linear Algebra
• MA 447 - Number Theory
• MA 448 - Graph Theory
• MA 481 - Operations Research
• MA 483 - Numerical Optimization
• MA 485 - Stochastic Processes
• MA 489 - Techniques of Mathematical Modeling
• MA 490 - Special Topics in Mathematics
• MA 499 - Mathematics Internship

• ST 110 - Introduction to Statistical Methods and Data Analysis
• ST 200 - Opportunities in STEM
• ST 210 - Introduction to Statistics
• ST 265 - Biostatistics
• ST 310 - Statistical Computing
• ST 381 - Probability and Statistics
• ST 461 - Elements of Statistical Theory I: Distributions
• ST 462 - Elements of Statistical Theory II: Inference
• ST 465 - Experimental Research Methods
• ST 466 - Experimental Design
• ST 471 - Statistical Quality Control
• ST 472 - Applied Multivariate Analysis
• ST 473 - Statistical Learning and Big Data
• ST 475 - Survival Analysis and Generalized Linear Models
• ST 485 - Stochastic Processes
• ST 491 - Special Topics in Statistics
• ST 499 - Statistics Internship

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