Union, Intersection, Independence, Disjoint, Complement: Superior Likelihood for Knowledge Science Sequence (1)
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For those who’ve been following my earlier articles within the chance sequence, you could have observed that I briefly touched on ideas like probability 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 idea for all chance calculations such because the Union, Intersection, Independence, Disjoint, and so on.
These notations aren’t simply one thing that needs to be brushed over as a result of they’re tremendous necessary in all issues associated to information. Particularly in fields like information 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 strong understanding of the fundamentals.
With out this basis, superior chance…