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  2. Law of large numbers - Wikipedia

    en.wikipedia.org/wiki/Law_of_large_numbers

    They are called the strong law of large numbers and the weak law of large numbers. [ 16 ] [ 1 ] Stated for the case where X 1 , X 2 , ... is an infinite sequence of independent and identically distributed (i.i.d.) Lebesgue integrable random variables with expected value E( X 1 ) = E( X 2 ) = ... = μ , both versions of the law state that the ...

  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. Empirical statistical laws - Wikipedia

    en.wikipedia.org/wiki/Empirical_statistical_laws

    However, both types of "law" may be considered instances of a scientific law in the field of statistics. What distinguishes an empirical statistical law from a formal statistical theorem is the way these patterns simply appear in natural distributions , without a prior theoretical reasoning about the data.

  5. Statistical regularity - Wikipedia

    en.wikipedia.org/wiki/Statistical_regularity

    It is an umbrella term that covers the law of large numbers, all central limit theorems and ergodic theorems. If one throws a dice once, it is difficult to predict the outcome, but if one repeats this experiment many times, one will see that the number of times each result occurs divided by the number of throws will eventually stabilize towards ...

  6. Law of the iterated logarithm - Wikipedia

    en.wikipedia.org/wiki/Law_of_the_iterated_logarithm

    The law of iterated logarithms operates "in between" the law of large numbers and the central limit theorem.There are two versions of the law of large numbers — the weak and the strong — and they both state that the sums S n, scaled by n −1, converge to zero, respectively in probability and almost surely:

  7. Kronecker's lemma - Wikipedia

    en.wikipedia.org/wiki/Kronecker's_lemma

    The lemma is often used in the proofs of theorems concerning sums of independent random variables such as the strong Law of large numbers. The lemma is named after the German mathematician Leopold Kronecker .

  8. List of logarithmic identities - Wikipedia

    en.wikipedia.org/wiki/List_of_logarithmic_identities

    The harmonic numbers are a fundamental sequence in number theory and analysis, known for their logarithmic growth. This result leverages the fact that the sum of the inverses of integers (i.e., harmonic numbers) can be closely approximated by the natural logarithm function, plus a constant, especially when extended over large intervals.

  9. Littlewood's law - Wikipedia

    en.wikipedia.org/wiki/Littlewood's_law

    Littlewood’s law of miracles states that in the course of any normal person’s life, miracles happen at a rate of roughly one per month. The proof of the law is simple. During the time that we are awake and actively engaged in living our lives, roughly for 8 hours each day, we see and hear things happening at a rate of about one per second.