Statistical anomalies and understanding the difference between an anomaly, a trend, etc. Is how statistics work. It's exactly how they work. I've already said this once, but I don't get your argument. It sounds like you are saying we should assume this is the new normal even though we just have one year's worth of data. That isn't how statistics work, and any scientist or data analyst or anyone else with a background in data would tell you that you are incorrectly jumping to conclusions.

No offense, but it seems like the argument has gone over your head.

Yes, if crime went up 500% in one year it would be a statistical anomaly. The argument is that you can't draw conclusions from a single years worth of data. If next year there are again 5 murders or even more then we can gain confidence that this is a trend, but again, we'd need more data.

A statistical anomaly is simply a number that is much greater than normal. If it becomes the norm (I. E. Over the years this rate of murder becomes typical) then it would no longer be an anomaly.

Another example that may help is football. Let's say the Pats score 17 points per game, on average, over the first ten games of the season and then score 45 in week 11. Do you assume that they will continue scoring 45 or similarly high scores moving forward? Or do you assume it's a blip?

My assumption here is that you would assume it's a blip BUT if the Pats continues to score that much week-after-week you could determine that something has changed. You simply can't assume that because murders were high in one year that it will continue, especially when historically murders are low or non-existent. It's an outlier.

I'm not sure what exactly your argument is but it doesn't make sense from a scientific standpoint. You may be confident this is the new norm in Burlington but until the data backs that up with multiple years of a similar trend all you are doing is jumping to conclusions.

I don't understand why you don't get that, but hopefully this helped a bit.