Here’s another combinatorial identity that I think should be useful, and one that I will probably run into again:
, which allows you to compute very useful sums like:
. Combined with Stirling’s formula, this sum is asymptotically
.
For example, consider the standard simple, one dimensional random walk, where one can move left or right with equal probability. The expected location after steps is 0, but the expected distance after
steps is
, which can be arrived at via the identities described above. The standard deviation of the location is exactly
. Does any one know of a precise relationship between the variance and the expected distance?
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Another useful identity:
And another:
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Taylor series expansion for
, where
is the binary entropy function: