- UNM Catalog 2021-2022
- >Colleges
- >College of Arts and Sciences
- >Mathematics and Statistics

M. Cristina Pereyra, Chair

Department of Mathematics and Statistics

Science and Math Learning Center

MSC01 1115

1 University of New Mexico

Albuquerque, NM 87131-0001

(505) 277-4613

**Professors**Matthew Blair, Ph.D., University of Washington

Alexandru Buium, Ph.D., University of Bucharest (Romania)

Ronald Christensen, Ph.D., University of Minnesota

Gabriel Huerta, Ph.D., Duke University

Jens Lorenz, Ph.D., University of Münster (Germany)

Terry A. Loring, Ph.D., University of California, Berkeley

Pavel M. Lushnikov, Ph.D., L.D. Landau Institute for Theoretical Physics of the Russian Academy of Sciences

Michael J. Nakamaye, Ph.D., Yale University

Monika Nitsche, Ph.D., University of Michigan

Maria C. Pereyra, Ph.D., Yale University

Deborah L. Sulsky, Ph.D., New York University

Dimiter Vassilev, Ph.D., Purdue University

Helen Wearing, Ph.D., Heriot-Watt University (Scotland)

**Associate Professors**

James Degnan, Ph.D., University of New Mexico

Erik B. Erhardt, Ph.D., University of New Mexico

Hongnian Huang, Ph.D., University of Wisconsin, Madison

Alexander O. Korotkevich, Ph.D., L.D. Landau Institute for Theoretical Physics of the Russian Academy of Sciences

Stephen Lau, Ph.D., University of North Carolina, Chapel Hill

Li Li, Ph.D., University of South Carolina

Yan Lu, Ph.D., Arizona State University

Mohammad Motamed, Ph.D., Royal Institute of Technology (Sweden)

Anna Skripka, Ph.D., University of Missouri

Janet Vassilev, Ph.D., University of California, Los Angeles

Guoyi Zhang, Ph.D., University of Arizona

Maxim Zinchenko, Ph.D., University of Missouri

**Assistant Professors**

Jehanzeb H. Chaudhry, Ph.D., University of Illinois Urbana, Champaign

Fletcher Christensen, Ph.D., University of California, Irvine

Jacob Schroeder, Ph.D., University of Illinois Urbana, Champaign

**Lecturers**Timothy Berkopec, M.S., University of Illinois, Urbana

Jurg Bolli, M.S., University of Zurich (Switzerland)

Karen Champine, M.A., University of New Mexico

Nina Greenberg, M.S., University of New Mexico

Derek Martinez, Ph.D., University of New Mexico

Patricia Oakley, Ph.D., Northwestern University

Kathleen Sorensen, M.S., University of Alaska, Fairbanks

Karen Sorensen-Unruh, M.S., University of New Mexico

**Professors Emeriti/Retired**

Charles P. Boyer, Ph.D., Pennsylvania State University

Evangelos A. Coutsias, Ph.D., California Institute of Technology

James A. Ellison, Ph.D., California Institute of Technology

Pedro F. Embid, Ph.D., University of California, Berkeley

Roger C. Entringer, Ph.D., University of New Mexico

Archie G. Gibson, Ph.D., University of Colorado

Frank L. Gilfeather, Ph.D., University of California, Irvine

Nancy A. Gonzales, Ed.D., Harvard University

Richard J. Griego, Ph.D., University of Illinois

Liang-Shin Hahn, Ph.D., Stanford University

Reuben Hersh, Ph.D., New York University

Wojciech Kucharz, Ph.D., Jagiellonian University (Poland)

Cornelis W. Onneweer, Ph.D., Wayne State University

Pramod K. Pathak, Ph.D., Indian Statistical Institute

Clifford R. Qualls, Ph.D., University of California, Riverside

Ronald M. Schrader, Ph.D., Pennsylvania State University

Stanly L. Steinberg, Ph.D., Stanford University

William J. Zimmer, Ph.D., Purdue University

Mathematics is fundamental to the formulation and analysis of scientific theories, is a rich and independent field of inquiry, and its study is excellent preparation for life in our highly specialized society. Active research throughout the mathematical sub-disciplines, spurred on in part by advances in computing technology, leads to new perspectives and applications. The major in mathematics combines broad study of fundamental theories with in-depth investigation of particular subjects chosen from pure, applied and computational mathematics. A degree in mathematics, either alone or in combination with study in another field, is excellent preparation for careers in industry, academia, and research institutes.

Statistics is the science of collecting and analyzing data. Statisticians interact with researchers in all the various disciplines of science, engineering, medicine, social science and business to develop scientifically sound methods in those areas. Most course work in the department is devoted to understanding current methods and the reasoning behind them. A degree in statistics prepares students for careers in industry, government, academia, and research institutes, as well as being excellent preparation for professional programs in medicine, law, business administration and public policy and administration.

**High School Students:** To prepare for college-level Mathematics or Statistics, high school students must take two years of algebra and one year of geometry prior to admission. Students should take mathematics during their senior year of high school and also take the ACT or SAT examination during that year, for the best preparation and placement into mathematics courses at the University of New Mexico. Students planning to major in any scientific or technological field should take advanced mathematics courses (Trigonometry, Pre-Calculus, Calculus, etc.) in high school. Placement in Mathematics or Statistics courses at UNM is based on the highest ACT/SAT Math scores or UNM Placement Exam Math scores.

A beginning student who wishes to take MATH 1522 or a more advanced course must have College Board Advanced Placement scores as described in the *Admissions* section of this Catalog.

A student who wishes to enroll in a course requiring a prerequisite must earn a grade of "C" (not "C-") or better in the prerequisite course.

1. Content on specific courses overlaps enough to necessitate restricting credit of both courses toward a student’s degree. These courses are not considered equivalent and the completion of the second course in a pair will not affect a student’s earned hours on the transcript. Students should consult their advisor if they feel the incorrect course is applied for credit on their degree audit.

Students will be allowed to apply only one of the following courses in each pair for credit towards a degree:

- MATH 1430 and MATH 1512.
- MATH 1440 and MATH 1522.
- MATH **314 and MATH **321.

2. Students who have credit for MATH 1220 College Algebra or higher may not then take MATH 1215X, 1215Y, and 1215Z Intermediate Algebra for credit.

3. Mathematics or Statistics coursework dating back more than five years cannot automatically be counted as fulfillment of a prerequisite. Students with older coursework take the placement exam offered through the University of New Mexico Testing Center to determine what Mathematics or Statistics courses to register for based on their skill level.

**Undergraduate courses in Mathematics (MATH) may be categorized as Introductory Course, or as Courses for Teachers and Education Students. Courses in these categories are identified in parenthesis at the end of the course description according to the following legend:**

**Introductory Courses (I), Courses for Teachers and Education Students (T).**

**
MATH 107.
Problems in College Algebra.
(1)
**

**
MATH 110.
Problems in Elements of Calculus.
(1)
**

**
MATH 1118.
Mathematics for Elementary and Middle School Teachers I.
(3)
**

**
MATH 1130.
Survey of Mathematics.
(3)
**

**
MATH 116.
Topics in Pre-Calculus Mathematics.
(1-6 to a maximum of 12 Δ)
**

**
MATH 1215X.
Intermediate Algebra IA.
(1)
**

**
MATH 1215Y.
Intermediate Algebra IB.
(1)
**

**
MATH 1215Z.
Intermediate Algebra IC.
(1)
**

**
MATH 1220.
College Algebra.
(3)
**

**
MATH 1230.
Trigonometry.
(3)
**

**
MATH 1240.
Pre-Calculus.
(3)
**

**
MATH 1250.
Trigonometry and Pre-Calculus.
(5)
**

**
MATH 1300.
Statistical Literacy.
(3)
**

**
MATH 1350.
Introduction to Statistics.
(3)
**

**
MATH 1430.
Applications of Calculus I.
(3)
**

**
MATH 1440.
Applications of Calculus II.
(3)
**

**
MATH 1512.
Calculus I.
(4)
**

**
MATH 1522.
Calculus II.
(4)
**

**
MATH 1996.
Topics.
(1-6, no limit Δ)
**

**
MATH 2115.
Math for Middle School Teachers.
(3)
**

**
MATH 2118.
Mathematics for Elementary and Middle School Teachers III.
(3)
**

**
MATH 2531 [2530].
Calculus III.
(4)
**

**
MATH 2996.
Topics.
(1-6, no limit Δ)
**

**
MATH 305 / 507.
Mathematics from a Historical Perspective.
(3)
**

**
MATH 306.
College Geometry.
(3)
**

**
MATH 311.
Vector Analysis.
(3)
**

**
MATH **312.
Partial Differential Equations for Engineering.
(3)
**

**
MATH **313.
Complex Variables.
(3)
**

**
MATH **314.
Linear Algebra with Applications.
(3)
**

**
MATH **316.
Applied Ordinary Differential Equations.
(3)
**

**
MATH **317.
Elementary Combinatorics.
(3)
**

**
MATH **319.
Theory of Numbers.
(3)
**

**
MATH **321.
Linear Algebra.
(3)
**

**
MATH 322.
Modern Algebra I.
(3)
**

**
MATH **327.
Introduction to Mathematical Thinking and Discrete Structures.
(3)
**

**
MATH 338 / 542.
Mathematics for Secondary Teachers.
(3)
**

**
MATH **356.
Symbolic Logic.
(4)
**

**
MATH **375.
Introduction to Numerical Computing.
(3)
**

**
MATH 391.
Advanced Undergraduate Honors Seminar.
(1-3 to a maximum of 8 Δ)
**

**
MATH 393.
Topics in Mathematics.
(3, no limit Δ)
**

**
MATH 401 / 501.
Advanced Calculus I.
(4)
**

**
MATH 402 / 502.
Advanced Calculus II.
(3)
**

**
MATH **412.
Nonlinear Dynamics and Chaos.
(3)
**

**
MATH **415.
History and Philosophy of Mathematics.
(3)
**

**
MATH *421.
Modern Algebra II.
(3)
**

**
MATH *431.
Introduction to Topology.
(3)
**

**
MATH **439.
Topics in Mathematics.
(1-3, no limit Δ)
**

**
MATH 441.
Probability.
(3)
**

**
MATH 462 / 512.
Introduction to Ordinary Differential Equations.
(3)
**

**
MATH 463 / 513.
Introduction to Partial Differential Equations.
(3)
**

**
MATH 464 / 514.
Applied Matrix Theory.
(3)
**

**
MATH *471.
Introduction to Scientific Computing.
(3)
**

**
MATH 472 / 572.
Fourier Analysis and Wavelets.
(3)
**

**
MATH 499.
Individual Study.
(1-3 to a maximum of 6 Δ)
**

**
MATH 501 / 401.
Advanced Calculus I.
(4)
**

**
MATH 502 / 402.
Advanced Calculus II.
(3)
**

**
MATH 504.
Introductory Numerical Analysis: Numerical Linear Algebra.
(3)
**

**
MATH 505.
Introductory Numerical Analysis: Approximation and Differential Equations.
(3)
**

**
MATH 507 / 305.
Mathematics from a Historical Perspective.
(3)
**

**
MATH 510.
Introduction to Analysis I.
(3)
**

**
MATH 511.
Introduction to Analysis II.
(3)
**

**
MATH 512 / 462.
Introduction to Ordinary Differential Equations.
(3)
**

**
MATH 513 / 463.
Introduction to Partial Differential Equations.
(3)
**

**
MATH 514 / 464.
Applied Matrix Theory.
(3)
**

**
MATH 519.
Selected Topics in Algebra and Number Theory.
(3, no limit Δ)
**

**
MATH 520.
Abstract Algebra I.
(3)
**

**
MATH 521.
Abstract Algebra II.
(3)
**

**
MATH 530.
Commutative Algebra.
(3)
**

**
MATH 531.
Algebraic Geometry.
(3)
**

**
MATH 532.
Algebraic Topology I.
(3)
**

**
MATH 533.
Algebraic Topology II.
(3)
**

**
MATH 535.
Foundations of Topology.
(3)
**

**
MATH 536.
Introduction to Differentiable Manifolds.
(3)
**

**
MATH 537.
Riemannian Geometry I.
(3)
**

**
MATH 538.
Riemannian Geometry II.
(3)
**

**
MATH 539.
Selected Topics in Geometry and Topology.
(3, no limit Δ)
**

**
MATH 540.
Stochastic Processes with Applications.
(3)
**

**
MATH 542 / 338.
Mathematics for Secondary Teachers.
(3)
**

**
MATH 549.
Selected Topics in Probability Theory.
(3, no limit Δ)
**

**
MATH 551.
Problems.
(1-3, no limit Δ)
**

**
MATH 557.
Selected Topics in Numerical Analysis.
(3, no limit Δ)
**

**
MATH 561.
Functions of a Complex Variable I.
(3)
**

**
MATH 562.
Functions of a Complex Variable II.
(3)
**

**
MATH 563.
Analysis III.
(3)
**

**
MATH 565.
Analysis IV.
(3)
**

**
MATH 569.
Selected Topics in Analysis.
(3, no limit Δ)
**

**
MATH 570.
Singular Perturbations.
(3)
**

**
MATH 572 / 472.
Fourier Analysis and Wavelets.
(3)
**

**
MATH 576.
Numerical Linear Algebra.
(3)
**

**
MATH 577.
Numerical Ordinary Differential Equations.
(3)
**

**
MATH 578.
Numerical Partial Differential Equations.
(3)
**

**
MATH 579.
Selected Topics in Applied Mathematics.
(3, no limit Δ)
**

**
MATH 581.
Functional Analysis I.
(3)
**

**
MATH 583.
Methods of Applied Mathematics I.
(3)
**

**
MATH 584.
Methods of Applied Mathematics II.
(3)
**

**
MATH 598.
Practicum.
(1-6 to a maximum of 6 Δ)
**

**
MATH 599.
Master's Thesis.
(1-6, no limit Δ)
**

**
MATH 605.
Graduate Colloquium.
(1, may be repeated three times Δ)
**

**
MATH 639.
Seminar in Algebra and Geometry.
(1-3, no limit Δ)
**

**
MATH 649.
Seminar in Probability and Statistics.
(1-3, no limit Δ)
**

**
MATH 650.
Reading and Research.
(1-6 to a maximum of 12 Δ)
**

**
MATH 669.
Seminar in Analysis.
(1-3, no limit Δ)
**

**
MATH 679.
Seminar in Applied Mathematics.
(1-3, no limit Δ)
**

**
MATH 699.
Dissertation.
(3-12, no limit Δ)
**

**
STAT 279.
Topics in Introductory Statistics.
(1-3 to a maximum of 3 Δ)
**

**
STAT **345.
Elements of Mathematical Statistics and Probability Theory.
(3)
**

**
STAT 427 / 527.
Advanced Data Analysis I.
(3)
**

**
STAT 428 / 528.
Advanced Data Analysis II.
(3)
**

**
STAT 434 / 534.
Contingency Tables and Dependence Structures.
(3)
**

**
STAT 440 / 540.
Regression Analysis.
(3)
**

**
STAT 445 / 545.
Analysis of Variance and Experimental Design.
(3)
**

**
STAT 453 / 553.
Statistical Inference with Applications.
(3)
**

**
STAT 461 / 561.
Probability.
(3)
**

**
STAT 470 / 570.
Industrial Statistics.
(3)
**

**
STAT 472 / 572.
Sampling Theory and Practice.
(3)
**

**
STAT 474 / 574.
Biostatistical Methods: Survival Analysis and Logistic Regression.
(3)
**

**
STAT 476 / 576.
Multivariate Analysis.
(3)
**

**
STAT 477 / 577.
Introduction to Bayesian Modeling.
(3)
**

**
STAT 479.
Topics in Statistics.
(3, no limit Δ)
**

**
STAT 481 / 581.
Introduction to Time Series Analysis.
(3)
**

**
STAT 495.
Individual Study.
(1-3 to a maximum of 6 Δ)
**

**
STAT 520.
Topics in Interdisciplinary Biological and Biomedical Sciences.
(3, no limit Δ)
**

**
STAT 527 / 427.
Advanced Data Analysis I.
(3)
**

**
STAT 528 / 428.
Advanced Data Analysis II.
(3)
**

**
STAT 534 / 434.
Contingency Tables and Dependence Structures.
(3)
**

**
STAT 540 / 440.
Regression Analysis.
(3)
**

**
STAT 545 / 445.
Analysis of Variance and Experimental Design.
(3)
**

**
STAT 546.
Theory of Linear Models.
(3)
**

**
STAT 547.
Multivariate Analysis and Advanced Linear Models.
(3)
**

**
STAT 553 / 453.
Statistical Inference with Applications.
(3)
**

**
STAT 556.
Advanced Statistical Inference I.
(3)
**

**
STAT 557.
Advanced Statistical Inference II.
(3)
**

**
STAT 561 / 461.
Probability.
(3)
**

**
STAT 565.
Stochastic Processes with Applications.
(3)
**

**
STAT 569.
Selected Topics in Probability Theory.
(3, no limit Δ)
**

**
STAT 570 / 470.
Industrial Statistics.
(3)
**

**
STAT 572 / 472.
Sampling Theory and Practice.
(3)
**

**
STAT 574 / 474.
Biostatistical Methods: Survival Analysis and Logistic Regression.
(3)
**

**
STAT 576 / 476.
Multivariate Analysis.
(3)
**

**
STAT 577 / 477.
Introduction to Bayesian Modeling.
(3)
**

**
STAT 579.
Selected Topics in Statistics.
(3, no limit Δ)
**

**
STAT 581 / 481.
Introduction to Time Series Analysis.
(3)
**

**
STAT 586.
Nonparametric Curve Estimation and Image Reconstruction.
(3)
**

**
STAT 590.
Statistical Computing.
(3)
**

**
STAT 595.
Problems.
(1-3, no limit Δ)
**

**
STAT 599.
Master's Thesis.
(1-6, no limit Δ)
**

**
STAT 605.
Graduate Colloquium.
(1, may be repeated three times Δ)
**

**
STAT 649.
Seminar in Probability and Statistics.
(1-3, no limit Δ)
**

**
STAT 650.
Reading and Research.
(1-6 to a maximum of 12 Δ)
**

**
STAT 699.
Dissertation.
(3-12, no limit Δ)
**

Office of the Registrar

MSC11 6325

1 University of New Mexico

Albuquerque, NM 87131

(505) 277-8900

Phone: (505) 277-6809

Fax: