Could you elaborate a bit? How do Bayesian methods avoid misinterpretation?
Bayesian treat parameter as a distribution.
The point estimate is base on sample space where as the parameter distribution is base the parameter space.
I think learning both is good and people who pit those two school of statistic against each other are a bit too zealot. They're both tools and use them as needed and when one is easier than the other.
You know that it's an underestimate because you have prior knowledge about cancer incidence. Bayesian methods let you incorporate that knowledge into estimation process, pulling the estimate up towards a more realistic value.
Undefined variance isn’t nice.