Frequentist only takes the given sample. Bayesian takes the given sample (observed evidence) and a prior belief and combine the two for posterior belief.
Example
What’s the failure rate 5 of the 100 bulbs failed?
Frequentist: 5% (taking only given dataset)
Bayesian: similar factories have a lot lower failure rate, let’s say 1% so than we add this new evidence and we say this factory probably has 2%.
So when observing any given reality it requires separating what is from what I would expect to see.
Example
Taking the simulation hypothesis Sean Carroll says he a) wouldn’t expect to see universe that big and b) wouldn’t expect to be rendered in this resolution. It would be too expensive to run simulation that large. That is if we were living in a simulation it would be much smaller.