![]() Luckily, the Central Limit Theorem offers us some insight into how many events we need for a good sample. Our calculations could produce either a lot of false positives or miss some anomalous events as a result. If we choose too small of a timeframe, we might not get a representative sample of the data. When calculating the statistics mentioned above, we need to make sure the sample size we’re choosing accurately represents the data. ![]() if the field contains the number of bytes transferred in the event). You’ll want to use this for numerical data (e.g. ![]()
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