Union, Intersection, Independence, Disjoint, Complement: Superior Likelihood for Information Science Collection (1)
19 hours in the past
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When you’ve been following my earlier articles within the likelihood collection, you might have seen that I briefly touched on ideas like likelihood notations earlier than diving into Bayes’ theorem.
I took a while to look again at my articles and realized that I didn’t go deeply into the foundational notations that set the premise for all likelihood calculations such because the Union, Intersection, Independence, Disjoint, and so on.
These notations aren’t simply one thing that ought to be brushed over as a result of they’re tremendous necessary in all issues associated to knowledge. Particularly in fields like knowledge evaluation, machine studying, and statistical modeling.
This realization led me to suppose: earlier than leaping headfirst into superior matters like Conditional Likelihood, Conditional Independence, Bayes’ Theorem, Markov Chains, or Monte Carlo strategies, it’s essential to have a stable understanding of the fundamentals.
With out this basis, superior likelihood…