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  2. Geometric mean - Wikipedia

    en.wikipedia.org/wiki/Geometric_mean

    The geometric mean can also be expressed as the exponential of the arithmetic mean of logarithms. [4] By using logarithmic identities to transform the formula, the multiplications can be expressed as a sum and the power as a multiplication:

  3. Log-normal distribution - Wikipedia

    en.wikipedia.org/wiki/Log-normal_distribution

    The geometric or multiplicative mean of independent, identically distributed, positive random variables shows, for , approximately a log-normal distribution with parameters = [⁡ ()] and = [⁡ ()] /, assuming is finite.

  4. Logarithmic mean - Wikipedia

    en.wikipedia.org/wiki/Logarithmic_mean

    The logarithmic mean of two numbers is smaller than the arithmetic mean and the generalized mean with exponent greater than 1. However, it is larger than the geometric mean and the harmonic mean, respectively. The inequalities are strict unless both numbers are equal.

  5. Logarithm - Wikipedia

    en.wikipedia.org/wiki/Logarithm

    Here M(x, y) denotes the arithmetic–geometric mean of x and y. It is obtained by repeatedly calculating the average (x + y)/2 (arithmetic mean) and (geometric mean) of x and y then let those two numbers become the next x and y. The two numbers quickly converge to a common limit which is the value of M(x, y).

  6. Logarithmic scale - Wikipedia

    en.wikipedia.org/wiki/Logarithmic_scale

    Semi-log plot of the Internet host count over time shown on a logarithmic scale. A logarithmic scale (or log scale) is a method used to display numerical data that spans a broad range of values, especially when there are significant differences between the magnitudes of the numbers involved.

  7. List of logarithmic identities - Wikipedia

    en.wikipedia.org/wiki/List_of_logarithmic_identities

    For example, two numbers can be multiplied just by using a logarithm table and adding. These are often known as logarithmic properties, which are documented in the table below. [2] The first three operations below assume that x = b c and/or y = b d, so that log b (x) = c and log b (y) = d. Derivations also use the log definitions x = b log b (x ...

  8. Geometric distribution - Wikipedia

    en.wikipedia.org/wiki/Geometric_distribution

    The Log-Likelihood Function is: ... Given a mean, the geometric distribution is the maximum entropy probability distribution of all discrete probability distributions.

  9. Weighted geometric mean - Wikipedia

    en.wikipedia.org/wiki/Weighted_geometric_mean

    The second form above illustrates that the logarithm of the geometric mean is the weighted arithmetic mean of the logarithms of the individual values. If all the weights are equal, the weighted geometric mean simplifies to the ordinary unweighted geometric mean.