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  2. Law of large numbers - Wikipedia

    en.wikipedia.org/wiki/Law_of_large_numbers

    In probability theory, the law of large numbers (LLN) is a mathematical law that states that the average of the results obtained from a large number of independent random samples converges to the true value, if it exists. [1] More formally, the LLN states that given a sample of independent and identically distributed values, the sample mean ...

  3. Law of truly large numbers - Wikipedia

    en.wikipedia.org/wiki/Law_of_truly_large_numbers

    The law of truly large numbers (a statistical adage), attributed to Persi Diaconis and Frederick Mosteller, states that with a large enough number of independent samples, any highly implausible (i.e. unlikely in any single sample, but with constant probability strictly greater than 0 in any sample) result is likely to be observed. [1]

  4. Central limit theorem - Wikipedia

    en.wikipedia.org/wiki/Central_limit_theorem

    The law of the iterated logarithm specifies what is happening "in between" the law of large numbers and the central limit theorem. Specifically it says that the normalizing function √ n log log n, intermediate in size between n of the law of large numbers and √ n of the central limit theorem, provides a non-trivial limiting behavior.

  5. Empirical statistical laws - Wikipedia

    en.wikipedia.org/wiki/Empirical_statistical_laws

    Empirical statistical laws. An empirical statistical law or (in popular terminology) a law of statistics represents a type of behaviour that has been found across a number of datasets and, indeed, across a range of types of data sets. [1] Many of these observances have been formulated and proved as statistical or probabilistic theorems and the ...

  6. Probability theory - Wikipedia

    en.wikipedia.org/wiki/Probability_theory

    Furthermore, the more often the coin is tossed, the more likely it should be that the ratio of the number of heads to the number of tails will approach unity. Modern probability theory provides a formal version of this intuitive idea, known as the law of large numbers. This law is remarkable because it is not assumed in the foundations of ...

  7. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    Probability theory. In probability theory and statistics, a normal distribution or Gaussian distribution is a type of continuous probability distribution for a real-valued random variable. The general form of its probability density function is The parameter is the mean or expectation of the distribution (and also its median and mode), while ...

  8. Law of averages - Wikipedia

    en.wikipedia.org/wiki/Law_of_averages

    The law of averages is the commonly held belief that a particular outcome or event will, over certain periods of time, occur at a frequency that is similar to its probability. [ 1 ] [ 2 ] Depending on context or application it can be considered a valid common-sense observation or a misunderstanding of probability.

  9. Large numbers - Wikipedia

    en.wikipedia.org/wiki/Large_numbers

    A standardized way of writing very large numbers allows them to be easily sorted in increasing order, and one can get a good idea of how much larger a number is than another one. To compare numbers in scientific notation, say 5×10 4 and 2×10 5, compare the exponents first, in this case 5 > 4, so 2×10 5 > 5×10 4.