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  2. Quadratic reciprocity - Wikipedia

    en.wikipedia.org/wiki/Quadratic_reciprocity

    Gauss published the first and second proofs of the law of quadratic reciprocity on arts 125–146 and 262 of Disquisitiones Arithmeticae in 1801.. In number theory, the law of quadratic reciprocity is a theorem about modular arithmetic that gives conditions for the solvability of quadratic equations modulo prime numbers.

  3. Natural number - Wikipedia

    en.wikipedia.org/wiki/Natural_number

    It follows from the definition that each natural number is equal to the set of all natural numbers less than it. This definition, can be extended to the von Neumann definition of ordinals for defining all ordinal numbers, including the infinite ones: "each ordinal is the well-ordered set of all smaller ordinals."

  4. Mathematics - Wikipedia

    en.wikipedia.org/wiki/Mathematics

    Mathematical notation is widely used in science and engineering for representing complex concepts and properties in a concise, unambiguous, and accurate way. This notation consists of symbols used for representing operations , unspecified numbers, relations and any other mathematical objects, and then assembling them into expressions and ...

  5. Marine chemistry - Wikipedia

    en.wikipedia.org/wiki/Marine_chemistry

    Marine chemistry, also known as ocean chemistry or chemical oceanography, is the study of the chemical composition and processes of the world’s oceans, including the interactions between seawater, the atmosphere, the seafloor, and marine organisms. [2]

  6. Sampling (statistics) - Wikipedia

    en.wikipedia.org/wiki/Sampling_(statistics)

    In social science research, snowball sampling is a similar technique, where existing study subjects are used to recruit more subjects into the sample. Some variants of snowball sampling, such as respondent driven sampling, allow calculation of selection probabilities and are probability sampling methods under certain conditions.

  7. Big data - Wikipedia

    en.wikipedia.org/wiki/Big_data

    Big data very often means 'dirty data' and the fraction of data inaccuracies increases with data volume growth." Human inspection at the big data scale is impossible and there is a desperate need in health service for intelligent tools for accuracy and believability control and handling of information missed. [ 85 ]

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