Expand the fourth power and take expected values. independence factors products involving distinct indices, and centering makes every term with an index occurring just once have expected value zero. The only surviving index patterns are four equal indices and two pairs. There are six orderings of each pair pattern, so
Uniform boundedness gives and . Hence
Identical distributions were never used: only independence, the common bound, and zero means are needed.
The summands are nonnegative, so monotone convergence theorem, equivalently Tonelli's theorem for a sum, gives
A nonnegative random variable with finite expected value is finite almost surely. Thus the displayed nonnegative series converges almost surely, forcing its individual terms to tend to zero. Taking fourth roots proves
This is a fourth-moment proof of a strong law of large numbers for these bounded independent variables, without an identical-distribution assumption.

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