From Simple English Wikipedia, the free encyclopedia
Applied mathematics
is a field of
mathematics
which uses mathematics to solve
problems
of other branches of
science
. The contrary notion is
pure mathematics
. There are many fields:
- Approximation theory
:
[1]
Sometimes it is not possible to get an exact solution to a problem, because this might take too long, or it may not be possible at all. Approximation theory looks at ways to get a solution which is close to the exact one, and which can be obtained faster.
- Numerical analysis
and
simulation
: This field investigates various algorithms to get approximations for mathematical problems.
[2]
[3]
[4]
[5]
The study of
numerical linear algebra
[6]
[7]
[8]
and
validated numerics
[9]
[10]
are also included in this field.
- Probability
and
Statistics
:
[11]
[12]
[13]
How likely is it that something will happen? - If a coin is flipped 100 times, and lands heads up 53 times, is this coin good for games of chance, or should another one be taken?
- Optimization
is about finding better solutions to problems.
[14]
- In
ecology
certain things are known about populations of animals or plants. This is usually called
Population model
. Biologists use them to tell how a population changes over time.
- ↑
Trefethen, L. N. (2019). Approximation theory and approximation practice. SIAM.
- ↑
Stoer, J., & Bulirsch, R. (2013). Introduction to numerical analysis. Springer Science & Business Media.
- ↑
Conte, S. D., & De Boor, C. (2017). Elementary numerical analysis: an algorithmic approach.
Society for Industrial and Applied Mathematics
.
- ↑
Greenspan, D. (2018). Numerical Analysis. CRC Press.
- ↑
Linz, P. (2019). Theoretical numerical analysis. Courier Dover Publications.
- ↑
Demmel, J. W. (1997). Applied numerical linear algebra.
SIAM
.
- ↑
Ciarlet, P. G., Miara, B., & Thomas, J. M. (1989). Introduction to numerical linear algebra and optimization. Cambridge University Press.
- ↑
Trefethen, Lloyd; Bau III, David (1997). Numerical Linear Algebra (1st ed.). Philadelphia:
SIAM
.
- ↑
Tucker, Warwick (2011). Validated Numerics: A Short Introduction to Rigorous Computations. Princeton University Press.
- ↑
Rump, S. M. (2010). Verification methods: Rigorous results using floating-point arithmetic. Acta Numerica, 19, 287-449.
- ↑
DeGroot, M. H., & Schervish, M. J. (2012). Probability and statistics. Pearson Education.
- ↑
Johnson, R. A., Miller, I., & Freund, J. E. (2000). Probability and statistics for engineers (Vol. 2000, p. 642p). London: Pearson Education.
- ↑
Walpole, R. E., Myers, R. H., Myers, S. L., & Ye, K. (1993). Probability and statistics for engineers and scientists (Vol. 5). New York: Macmillan.
- ↑
Intriligator, M. D. (2002). Mathematical optimization and economic theory.
Society for Industrial and Applied Mathematics
.
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