Points of significance: Bayesian statistics.

The article offers information on Bayesian inference by identifying a coin as fair or biased based on the outcome of tosses and treating the degree of bias as a population parameter. It focuses on differences between Bayesian and frequentist inference by using the reference of probability theory. It also mentions that Bayesian inference quantifies the uncertainty about the data-generating mechanism by the prior distribution.