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> The problem with correlations are that you need a large volume of data to suggest causation. We don’t have that. Just based on this sentence I have a hard ti

> The problem with correlations are that you need a large volume of data to suggest causation. We don’t have that. Just based on this sentence I have a hard time believing you really are a scientist as you claim. There is no requirement on large volume of data to suggest causation. In fact no amount of data and correlation by itself can establish causation, because they are very different concepts (Hence the correlation!=causation). You need mechanisms to explain the causations, and you need to verify the mechanisms. This has been done extensively for climate change. > Because of those claims of causation, the field has lost significant credibility I would say your claims lost you a lot of credibility just now.

lettergram 5y ago
That's fair and I understand that. My point, is we have trouble even suggesting causation. We have one event (industrialization) and one suspected effect (warming temps). Without another time-series of data for comparison we don't know what the natural state of the world even is given the margin of error (we're only talking 1-2 degrees C). We don't have the full dataset so effectively we're seeing two lines go up at the same time and claiming one is causing the other. We can't even really make a correlation case, besides to say these two time series loosely correlate. Put another way, we suspect one event causes another, which are tracked via a time series. Normally, when you're discussing causality you'd looking for multiple instances of said event causing another. We don't have that. Hence, we're effectively shooting in the dark.