Should our beliefs be formed through strict Bayesian computations or Bayes' rule may be just a broad guideline to the formation of our beliefs.
Bayesian statistics is a subset of the field of statistics in which the evidence about the true state of the world is expressed in terms of degrees of belief or, more specifically, Bayesian probabilities. Such an interpretation is only one of a number of interpretations of probability and there are other statistical techniques that are not based on "degrees of belief". One formulation of the "key ideas of Bayesian statistics" is "that probability is orderly opinion, and that inference from data is nothing other than the revision of such opinion in the light of relevant new information."
[Edwards W, Lindman H, Savage LJ: Bayesian statistical inference for psycho-logical research. Psychological Review, 1963; 70:193-242 (quote: pp 519-520). Cited as per Dennis Fryback's preface in A. O’Hagan, B. Luce: A primer on Baysian Statistics in Health Economics and Outcomes Research. 2003. Published by the Bayesian Initiative in Health Economics & Outcomes Research and the Centre for Bayesian Statistics in Health Economics. Accessed June 9, 2015.]
Sir, I will take the example of the Monty Hall Problem to illustrate my view. It is not a severe mistake if an individual attempts it and chooses not to change his/her decision after the first door is opened. But if a person attempts it 3000 times (all independently) and if the number of times the decision is changed is significantly less than 2000, it is a case of ignorance - a blunder. This is where theory meets practice.
On the lighter side, we blindly believe (without questioning) few things to be true/existing just because a whopping majority believe so. Humans are naive Bayesians.
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