What if I told you I can show you the difference between Bayesian and Frequentist statistics with one single coin toss?

SUMMARY
It is only by insisting that the parameter may not be a random variable (Frequentist) that it makes any kind of sense to talk about your method's ability to deliver the right answer. As soon as you let the parameter be a random variable (Bayesian), there's no longer any notion of right and wrong.   

BAYES VS FREQUENTIST... FIGHT!
Visit my blog (http://bit.ly/quaesita_fvsb) for answers to the questions below.

What words tell you that we're wading through their territory?
What are they using statistics to change their minds about?
What is the main difference?
What do you win if you choose this side?
What do you lose if you choose this side?
So, which one is better?
Okay... so which one is more objective and "correct"?
What about small vs large sample sizes as a criterion?
Cassie, you're killing us here. Are you Bayesian or Frequentist?
Should I pick a side?

Learn more:
Frequentist vs Bayesian fight - your questions answered: http://bit.ly/quaesita_fvsb
8min statistics intro: http://bit.ly/quaesita_statistics
Statistical Thinking playlist: http://bit.ly/statthinking
Controversy about p-values: http://bit.ly/quaesita_needles