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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:
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.
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.
The computational complexity of computing the natural logarithm using the arithmetic-geometric mean (for both of the above methods) is (() ). Here, n is the number of digits of precision at which the natural logarithm is to be evaluated, and M ( n ) is the computational complexity of multiplying two n -digit numbers.
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.
In general, logarithms can be calculated using power series or the arithmetic–geometric mean, or be retrieved from a precalculated logarithm table that provides a fixed precision. [ 45 ] [ 46 ] Newton's method , an iterative method to solve equations approximately, can also be used to calculate the logarithm, because its inverse function, the ...
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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 ...