Applied mathematics

Applied mathematics is a branch of mathematics that concerns itself with the mathematical techniques typically used in the application of mathematical knowledge to other domains.

Contents 1 Divisions of applied mathematics 2 Utility of applied mathematics 3 Status in academic departments 4 Other mathematical sciences (associated with applied mathematics) 4.1 Scientific computing 4.2 Computer Science 4.3 Operations research and management science 4.4 Statistics 4.5 Actuarial science 4.6 Other disciplines 5 See also 6 References 7 External links

Divisions of applied mathematics

There is no consensus of what the various branches of applied mathematics are. Such categorizations are made difficult by the way mathematics and science change over time, and also by the way universities organize departments, courses, and degrees.

Historically, applied mathematics consisted principally of applied analysis, most notably differential equations, approximation theory (broadly construed, to include representations, asymptotic methods, variational methods, and numerical analysis), and applied probability. These areas of mathematics were intimately tied to the development of Newtonian Physics, and in fact the distinction between mathematicians and physicists was not sharply drawn before the mid-19th century. This history left a legacy as well; until the early 20th century subjects such as classical mechanics were often taught in applied mathematics departments at American universities rather than in physics departments, and fluid mechanics may still be taught in applied mathematics departments.^[1]

Today, the term applied mathematics is used in a broader sense. It includes the classical areas above, as well as other areas that have become increasingly important in applications. Even fields such as number theory that are part of pure mathematics are now important in applications (such as cryptology), though they are not generally considered to be part of the field of applied mathematics per se. Sometimes the term applicable mathematics is used to distinguish between the traditional field of applied mathematics and the many more areas of mathematics that are applicable to real-world problems.

Mathematicians distinguish between applied mathematics, which is concerned with mathematical methods, and the applications of mathematics within science and engineering. A biologist using a population model and applying known mathematics would not be doing applied mathematics, but rather using it. However, nonmathematicians do not usually draw this distinction. The use of mathematics to solve industrial problems is called industrial mathematics.^[2] Industrial mathematics is sometimes split in two branches: techno-mathematics (covering problems coming from technology) and econo-mathematics (for problems in economy and finance).^[3]

The success of modern numerical mathematical methods and software has led to the emergence of computational mathematics, computational science, and computational engineering, which use high performance computing for the simulation of phenomena and solution of problems in the sciences and engineering. These are often considered interdisciplinary programs.

Utility of applied mathematics

Historically, mathematics was most important in the natural sciences and engineering. However, after World War II, fields outside of the physical sciences have spawned the creation of new areas of mathematics, such as game theory, which grew out of economic considerations, or neural networks, which arose out of the study of the brain in neuroscience, or bioinformatics, from the importance of analyzing large data sets in biology.

The advent of the computer has created new applications, both in studying and using the new computer technology itself (computer science, which uses combinatorics, formal logic, and lattice theory), as well as using computers to study problems arising in other areas of science (computational science), and of course studying the mathematics of computation (numerical analysis). Statistics is probably the most widespread application of mathematics in the social sciences, but other areas of mathematics are proving increasingly useful in these disciplines, especially in economics and management science.

Status in academic departments

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Academic institutions are not consistent in the way they group and label courses, programs, and degrees in applied mathematics. At some schools, there is a single mathematics department, whereas others have separate departments for Applied Mathematics and (Pure) Mathematics. It is very common for Statistics departments to be separate at schools with graduate programs, but many undergraduate-only institutions include statistics under the mathematics department.

Many applied mathematics programs (as opposed to departments) consist of primarily cross-listed courses and jointly-appointed faculty in departments representing applications. Some Ph.D. programs in applied mathematics require little or no coursework outside of mathematics, while others require substantial coursework in a specific area of application. In some respects this difference reflects the distinction between "application of mathematics" and "applied mathematics".

Some universities in the UK host departments of Applied Mathematics and Theoretical Physics, but it is now much less common to have separate departments of pure and applied mathematics. A notable exception to this is the Department of Applied Mathematics and Theoretical Physics at the University of Cambridge, housing the Lucasian Professor of Mathematics whose incumbents include Isaac Newton, Charles Babbage, James Lighthill, Paul Dirac and Stephen Hawking.

Schools with separate applied mathematics departments range from Brown University, which has a well-known and large Division of Applied Mathematics that offers degrees through the doctorate, to Santa Clara University, which offers only the M.S. in applied mathematics^{[citation needed]}. Research universities dividing their mathematics department into pure and applied sections include Harvard and MIT.

At some universities there is some tension between applied and pure mathematics departments. One reason is that pure mathematics is often perceived as having a higher intellectual standing. Another reason is a different level of compensation, as applied mathematicians are often paid more. Applied mathematics also enjoys better opportunities to bring external funding from many sources, not limited to the Division of Mathematical Sciences at the National Science Foundation (NSF) like much of pure mathematics. External funding is highly valued at research universities and is often a condition for faculty advancement. Similar tensions can also exist between statistics and mathematics groups and departments.

Other mathematical sciences (associated with applied mathematics)

Applied mathematics is closely related to other mathematical sciences.

Scientific computing

Scientific computing includes applied mathematics (especially numerical analysis), computing science (especially high-performance computing, and mathematical modelling in a scientific discipline.

Computer Science

Computer science relies on logic, algebra, and combinatorics.

Operations research and management science

Operations research and management science are often taught in faculties of engineering, business, public policy.

Statistics

Applied mathematics has substantial overlap with the discipline of statistics. Statistical theorists study and improve statistical procedures with mathematics, and statistical research often raises mathematical questions. Statistical theory relies on probability and decision theory, and makes extensive use of scientific computing, analysis, and optimization; for the design of experiments, statisticians use algebra and combinatorics. Applied mathematicians and statisticians often work in a department of mathematical sciences (particularly at colleges and small universities).

Statisticians have long complained that many mathematics departments have assigned mathematicians (without statistical competence) to teach statistics courses, effectively giving "double blind" courses.^[4] Examining data from 2000, Schaeffer and Stasny^[5] reported

By far the majority of instructors within statistics departments have at least a master’s degree in statistics or biostatistics (about 89% for doctoral departments and about 79% for master’s departments). In doctoral mathematics departments, however, only about 58% of statistics course instructors had at least a master’s degree in statistics or biostatistics as their highest degree earned. In master’s-level mathematics departments, the corresponding percentage was near 44%, and in bachelor’s-level departments only 19% of statistics course instructors had at least a master’s degree in statistics or biostatistics as their highest degree earned. As we expected, a large majority of instructors in statistics departments (83% for doctoral departments and 62% for master’s departments) held doctoral degrees in either statistics or biostatistics. The comparable percentages for instructors of statistics in mathematics departments were about 52% and 38%.

This unprofessional conduct violates the "Statement on Professional Ethics" of the American Association of University Professors (which has been affirmed by many colleges and universities in the USA) and the ethical codes of the International Statistical Institute and the American Statistical Association. The principle that statistics-instructors should have statistical competence has been affirmed by the guidelines of the Mathematical Association of America, which has been endorsed by the American Statistical Association.^[6]

Actuarial science

Actuarial science uses probability, statistics, and economic theory.

Other disciplines

The line between applied mathematics and specific areas of application is often blurred. Many universities teach mathematical and statistical courses outside of the respective departments, in departments and areas including business and economics, engineering, physics, psychology, biology, computer science, and mathematical physics.

See also

• Computational engineering

References

1. ^ Stolz, M. (2002), "The History Of Applied Mathematics And The History Of Society", Synthese 133 (1): 43–57, http://www.springerlink.com/index/T152575218M865W4.pdf, retrieved on 2009-07-07 
2. ^ University of Strathclyde (17 January 2008), Industrial Mathematics, http://www.maths.strath.ac.uk/applying/postgraduate/research_topics/industrial_mathematics, retrieved on 8 January 2009 .
3. ^ European Consortium for Mathematics in Industry (ECMI), ECMI Postgraduate Programmes, http://www.ecmi-indmath.org/edu/index.php, retrieved on 8 January 2008 .
4. ^ The principle that college-instructors should have qualifications and engagement with their academic discipline has long been violated in United States colleges and universities, according to generations of statisticians:
   • Harold Hotelling (Dec. 1940). "The Teaching of Statistics". The Annals of Mathematical Statistics 11 (4): pp. 457-470. http://www.jstor.org/stable/2235726. 
   • Harold Hotelling (1988). "Golden Oldies: Classic Articles from the World of Statistics and Probability: 'The Teaching of Statistics'". Statistical Science 3 (1): pp. 63-71. doi:10.1214/ss/1177013001. http://projecteuclid.org/euclid.ss/1177013001. 
   • Harold Hotelling (1988). "Golden Oldies: Classic Articles from the World of Statistics and Probability: 'The Place of Statistics in the University'". Statistical Science 3 (1): pp. 72-83. doi:10.1214/ss/1177013002. http://projecteuclid.org/euclid.ss/1177013002. 
   These reprinted articles are followed by the comments of Kenneth J. Arrow, W. Edwards Deming, Ingram Olkin, David S. Moore, James V. Sidek, Shanti S. Gupta, Robert V. Hogg, Ralph A. Bradley, and by Harold Hotelling, Jr. (an economist and son of Harold Hotelling) in the same issue of Statistical Science.
5. ^ The qualifications of instructors in statistics have been examined (using data from 2000):
   • Scheaffer, Richard L. Scheaffer and Stasny, Elizabeth A (November 2004). "The State of Undergraduate Education in Statistics: A Report from the CBMS". The American Statistician 58 (4): pp. 265--271. doi:10.1198/000313004X5770. 
6. ^ The unprofessional teaching of statistics by mathematicians (without qualifications in statistics) has been addressed in many articles:
   • Moore, David S (Jan. 1988). "Should Mathematicians Teach Statistics?". The College Mathematics Journal 19 (1): pp. 3-7. http://www.jstor.org/stable/2686686. 
   • Cobb, George W. and Moore, David S (Nov. 1997). "Mathematics, Statistics, and Teaching". The American Mathematical Monthly 104 (9): pp. 801-823. http://www.jstor.org/stable/2975286. 

External links

• The Society for Industrial and Applied Mathematics (SIAM) is a professional society dedicated to promoting the interaction between mathematics and other scientific and technical communities. Aside from organizing and sponsoring numerous conferences, SIAM is a major publisher of research journals and books in applied mathematics.

v • d • e Major topics in Applied mathematics Applied analysis Approximation theory • Numerical analysis • Dynamical systems • Control theory • Chaos theory Discrete mathematics Combinatorics • Graph theory • Game theory • Discrete geometry • Computability theory • Complexity theory • Information theory • Cryptography Probability Probability distribution • Probability theory • Statistics • Stochastic process • Operations research Other areas Optimization • Cryptography • Financial mathematics • Theoretical computer science • Mathematical biology • Mathematical chemistry • Mathematical economics • Mathematical physics • Mathematical psychology • Mathematical sociology

v • d • e Major fields of mathematics Logic · Set theory · Category theory · Algebra (elementary – linear – abstract) · Number theory · Analysis/Calculus · Geometry · Topology · Dynamical systems · Combinatorics · Game theory · Information theory · Numerical Analysis · Optimization · Computation · Probability · Statistics