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Quantitative research is a research strategy ... between empirical observation and mathematical expression of quantitative ... provide reasoning behind participants ...
[f] [177] Rigorous reasoning is not specific to mathematics, but, in mathematics, the standard of rigor is much higher than elsewhere. Despite mathematics' concision, rigorous proofs can require hundreds of pages to express, such as the 255-page Feit–Thompson theorem.
Mathematical statistics is the application of probability theory and other mathematical concepts to statistics, as opposed to techniques for collecting statistical data. [1] Specific mathematical techniques that are commonly used in statistics include mathematical analysis , linear algebra , stochastic analysis , differential equations , and ...
Ulugh Beg's meridian arc for precise astronomical measurements (15th c.). The exact sciences or quantitative sciences, sometimes called the exact mathematical sciences, [1] are those sciences "which admit of absolute precision in their results"; especially the mathematical sciences. [2]
The expression "mathematical proof" is used by lay people to refer to using mathematical methods or arguing with mathematical objects, such as numbers, to demonstrate something about everyday life, or when data used in an argument is numerical. It is sometimes also used to mean a "statistical proof" (below), especially when used to argue from data.
In 2015, Liang and two of his classmates from Zhejiang University created a quantitative hedge fund, High-Flyer, whose website says it "relies on mathematics and AI for quantitative investment."
The process of developing a mathematical model is termed mathematical modeling. Mathematical models are used in applied mathematics and in the natural sciences (such as physics , biology , earth science , chemistry ) and engineering disciplines (such as computer science , electrical engineering ), as well as in non-physical systems such as the ...
Uncertainty quantification (UQ) is the science of quantitative characterization and estimation of uncertainties in both computational and real world applications. It tries to determine how likely certain outcomes are if some aspects of the system are not exactly known.