I am aware that the geometric mean is often used with the lognormal distribution, because then it directly relates to the arithmetic mean with the normal distribution.
But I was trying to think of an intuitive defintion of the geometric mean.
For example, the median can be explained as "the data point such that half of the data points have higher values and the other half have lower values."
Is there a similar definition for the geometric mean?
This is of course not a 'non-mathematical definition', but I hope it is quite intuitive...
A geometric mean (see Wikipedia) of values $A$ and $B$ is a value $Q=\sqrt{A\cdot B}$, such that a square with side $Q$ has an area equal to that of a rectangle $A$ by $B$.
For more variables, a geometric mean of values $x_1, x_2, \ldots x_n$ is $$\sqrt[n]{x_1\cdot x_2 \cdot \ldots \cdot x_n}$$ which is a length of the edge of an $n$–dimensional hypercube, which has the same (hyper)volume as a (hyper)cuboid with edges' lengths $x_1, x_2, \ldots x_n$.