Statistics 510 Applied Regression Analysis has been replaced by Statistics 410, R Programming and Data Science.
Statistics 410 is a required course in the Statistics Major with an Emphasis in Data Science. For the general Statistics Major, Statistics 410 will be included in the list of twelve units selected from Statistics 325, 496, 510, 520, 560, 575, 580, and 596. For the Statistics Major with an Emphasis in Actuarial Science, Statistics 410 will be included in the list of three units selected from Statistics 325, 410, 496, 560, and 596.
MATH 340 is a substitute for MATH 541 for the 2018/19 academic year.
Mathematics Course Renumbering
Course Title |
Old Number |
New Number |
Abstract Algebra |
Math 521A |
Math 320 |
Advanced Calculus I |
Math 534A |
Math 330 |
Programming in Mathematics |
Math 541/242 |
Math 340 |
Algebraic Structures |
Math 521B |
Math 520 |
Advanced Calculus II |
Math 534B |
Math 530 |
Example 534A is equivalent to 330, take only one of these.
In order to make the path to a Mathematics Bachelor’s degree clearer, several core courses were renumbered from 500 to 300-level. Mathematics majors should complete the 300-level courses right after completion of their required lower division classes. Thus, following Math 245, 252, and 254, Mathematics majors should next take the core courses in Abstract Algebra (MATH 320), Advanced Calculus (MATH 330), Differential Equations (MATH 337), and Numerical Analysis (MATH 340).
The core courses give a broad understanding of mathematics, and more formal training than lower division courses provide. They build a strong foundation for student success at the 500-level.
rev: 03/14/2018
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Naveen comes to us from the University of Missouri –Kansas City. Before joining UMKC, he had four years of postdoctoral research experience in Mathematical Biology working with Dr. Alan Perelson, Senior Fellow at the Los Alamos National Laboratory, and Dr. Lindi Wahl, professor at the University of Western Ontario. He has research experience in applied mathematics (mathematical biology), focused on application areas such as within-host viral dynamics, immunology, disease epidemiology, disease ecology and medicine, and on techniques such as mathematical and computational modeling, ordinary differential equations, partial differential equations, delay differential equations, optimal control,data fitting, and biostatistics. His publications are in diverse journals, from mathematical journals to computational, biological, public health, and medical journals. He has a network of collaborations with medical doctors and experimentalists at UMKC School of Pharmacy, University of California, San Francisco, University of California, Davis, University of North Carolina at Chapel Hill, and Duke University.
Naveen has a bachelor’s degree in mathematics, physics, and chemistry and a master’s in pure mathematics from Tribhuvan University in Kathmandu, Nepal. He taught mathematics and science at schools in Nepal while obtaining these degrees and then worked as a faculty member at Tribhuvan University. He obtained his PhD from York University in Toronto in 2008, and his thesis “Membrane Fusion between an Influenza Virus and a Healthy Cell: Mathematical Models” won the Susan Mann Dissertation Award and was nominated for the Faculty of Graduate Studies award. Naveen continues to maintain ties with Nepal, and he is the current President of Association of Nepalese Mathematicians in America. He served on an interdisciplinary curriculum development committee for undergraduate mathematics courses at Tribhuvan University, and he helped organize a recent Society for Mathematics Biology- and CDC-supported Biomath Workshop in Kathmandu.
Naveen’s latest publication “Modeling Pharmacodynamics on HIV Latent Infection: Choice of Drugs is Key to Successful Cure via Early Therapy” just appeared in the SIAM Journal on Applied Mathematics, http://epubs.siam.org/doi/10.1
and was featured in the SIAM News
https://sinews.siam.org/Detail
and at Phys.org https://phys.org/news/2017-10-
This emphasis is designed to train the student in those areas of mathematics that may be applied to formulate and solve problems in other disciplines. The program is designed to qualify the student for employment as an applied mathematician, but the graduate would be well qualified for graduate study in pure or applied mathematics. The requirements include courses in statistics, computer programming and both theoretical and applied mathematics. The student also takes at least 12 units of a science in order to acquire some knowledge of a field to which mathematics can be applied. This will provide a good background for employment or for graduate work in applied mathematics or in that science. For example, a math major with 4 upper division courses in Economics would be able to pursue graduate work in Economics.
Preparation for the Major and Additional Coursework Required
Three semesters of Calculus (Math 150,151 and 252); Math Software Workshop (Math 242); Discrete Mathematics (Math 245); Linear Algebra (Math 254); Statistical Principles and Practices (Stat250) for a total of 24 units. Some lower division courses will probably be prerequisite to science courses applied to the major.
Major
A minimum of 36 upper division units to include Math 337, 534A, 524 or 543, 532 or 534B; at least 6 units selected from Math 521A, 525, 531, 532, 537; 12 units from a science to which mathematics may be applied (these should be from a single science and must be approved by the B.S. adviser); and six units of electives in computer science, mathematics, or statistics, excluding Math 302, 303, 311, 312, 313, 315, 342A, 342B, 413, 414, 509, 510, Stat 357. Students must complete an outline for the major and file a copy signed by an adviser with the Office of the Registrar.
For more information on any of the BA/BS degrees contact the Mathematics Programs Advisor:
Dr. Carmelo Interlando, GMCS 581
interlan@mail.sdsu.edu
Dr. Joseph Mahaffy, GMCS 593
jmahaffy@mail.sdsu.edu
Emphasis in Applied Mathematics
Emphasis in Computational Science
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