A serious reasoning error that is particularly common among educated people is to argue that if a study hasn't been done on a particular question we have 'no data', and therefore no basis on which to form beliefs or act.

This is incorrect and dangerous. 1/

There is almost always a reference class we can use to make a sensible prediction, and often we can reason about the causal mechanism directly.

To see how this is clearly wrong, consider these two extreme cases: 2/

a. Before a vaccine trial is conducted we have 'no data' on how likely it is to work.

But we can estimate the likelihood just fine! To start with we can just check the base rate of all vaccine trials.

What fraction of all vaccine trials in history have had +ve results? 3/

That gives a much better estimate than pure agnosticism.

b. Imagine now that the vaccine trial results have come back positive. But by chance all the vaccines were given in a blue room.

So, will the vaccine still work if given in a red room? I guess we have 'no data'.

4/

So can we say nothing about about whether vaccines work in red rooms?

That is plainly ridiculous — we understand the causal mechanism and it doesn't involve room colour, so in fact we can give a near definitive answer to that question. 5/