Frequentist vs Bayesian View
Frequentist View
Defines probability of some event in terms of the relative frequency with which the event tends to occur
More widely used and usually involves simpler calculations
Frequentists think deductively: "If the true population looks like this, then my sample might look like this."
Terminology: p value, significant, null hypothesis, or confidence interval
Draw conclusions strictly from what’s in that set of given data
Bayesian View
Defines probability in more subjective terms — as a measure of the strength of your belief regarding the true situation
Requires powerful computers and sophisticated software
Bayesians think inductively: "My sample came out like this, so the true situation might be this."
Terminology: prior probability, noninformative priors, and credible intervals
Broader view of "usable information" which typically starts with some prior probabilities (based on previous experiments) and then blend in the results of the latest experiment to revise those probabilities
Note:
A population includes all of the elements from a set of data.
A sample consists one or more observations drawn from the population.
Link: - Dummies Series: TWO VIEWS OF PROBABILITY
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