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- * Let {{M|X\sim\text{Geometrically}(p)}} where {{M|p}} is the [[probability]] of an event happening. ** {{M|1=\mathbb{P}\left[X=n\right]=(1-p)^{n-1}p}} - that is the probability of an event not happing {{M|n-1}} times, then happening on the {{M|n^\text{968 B (171 words) - 19:37, 2 June 2016
- |title=Poisson distribution |data1=[[Discrete probability distribution|Discrete]], over {{M|\mathbb{N}_{\ge 0} }}8 KB (1,401 words) - 00:52, 20 July 2018
- : ''[[Probability frequency function]]'' and ''[[frequency function (probability)]]'' redirect here. A [[probability density function]] but for {{link|discrete probability distribution||s}}255 B (32 words) - 07:16, 20 September 2017
- There are a few distinct cases we may define the uniform distribution on, however in any case the concept is clear: ...the entire {{link|sample space|probability}}, here denoted {{M|S}}, of a [[probability space]] here denoted {{M|(S,\Omega,\mathbb{P})}}1 KB (192 words) - 05:41, 15 January 2018
- ...memoryless {{iff}} it's the [[exponential distribution]] - what about the discrete!}}{{ProbMacro}} ==Generalisation to a [[discrete random variable]]==1 KB (221 words) - 23:02, 11 November 2017
- :* [[Notes:Mdm of a discrete distribution lemma]] :* [[Notes:Mdm of a discrete distribution lemma - round 2]]{{ProbMacros}}2 KB (419 words) - 17:53, 24 January 2018