Bayesian statistics and frequentist statistics are the two pillars of quantitative probabilistic modeling. The frequentist approach is perhaps the easier of the two to grasp intuitively. Founded on the count-based modeling approach, it is premised on the hypothesis that the frequency of an event has a constant value that remains the same. The true parameter value is unique but unknown, and the experimental observations attempt to ferret out an estimate of this true parameter value.