Especially in the analysis of randomized algorithms, probabilistic bounds play a pivotal role in the proving of probabilistic theorems. This blog aims to be a reference for such key results that will be used in the randomized analyses conducted in upcoming blogs. Foremost, we cover the all-important Markov and Chebyshev
There are many methods of introducing structure to random variables in Probability Theory, and traditionally we call this structure a property, and one such property is its distribution. Phrases like “coming from this distribution” or “they distribute as such” or “these variables make this distribution” all refer to this property.