Alpha spending is a statistical method that distributes significance thresholds across interim checks in experiments. It prevents inflated false positives when results are evaluated multiple times before a test concludes.
This approach is common in medical trials but is also applied in digital optimization to preserve the validity of A/B test outcomes. By controlling how much significance is “spent” at each checkpoint, teams maintain reliable conclusions while still monitoring progress.
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