Difference between revisions of "Statistics notes  on random variables, distributions, probability"
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−  ===  +  ===Poisson distribution=== 
<!  <!  
−  +  Discrete  
+  Models te probability of a given number of events occurring,  
+  in a fixed interval of time or space,  
+  based on a known mean rate,  
+  independently of time since last even.  
+  
+  Used mainly if the events are relatively sparse; at higher rates it tends towards rh  
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Poisson  Poisson  
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* useful to model likeliness of something happening in an interval  that considers interval length, and the rarity of the events  * useful to model likeliness of something happening in an interval  that considers interval length, and the rarity of the events  
* for high rates, it starts to look more gaussian  * for high rates, it starts to look more gaussian  
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: Poisson  will be mostly two and one, sometimes three, more is fairly rare. Shape is not symmatric, and we want to model the rarity.  : Poisson  will be mostly two and one, sometimes three, more is fairly rare. Shape is not symmatric, and we want to model the rarity.  
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−  https://en.wikipedia.org/wiki/  +  
+  https://en.wikipedia.org/wiki/Poisson_distribution  
>  >  
−  ===  +  
+  ===Gaussian/Normal distribution===  
<!  <!  
−  +  Continuous  
−  https://en.wikipedia.org/wiki/  +  Gaussian distribution, a.k.a. Normal distribution 
+  
+  
+  Gaussian  
+  * many independent identical events  
+  * where things have a tendency to the average  
+  * support: real numbers  
+  * note: the combination of varying distributions converges on a gaussian (central limit theorem[https://en.wikipedia.org/wiki/Central_limit_theorem]), so it's a decent goto if you don't know.  
+  
+  Note that in various cases, more than one distribution can fit the data's nature {{comment(even when there is no real relation between the distributions. For example, for nontrivial counts both poisson and gaussian may work, which are quite different)}}.  
+  
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+  Examples:  
+  * height of body  
+  
+  
+  
+  https://en.wikipedia.org/wiki/Normal_distribution  
>  > 
Revision as of 18:13, 4 July 2020
This is more for overview of my own than for teaching or exercise.
Other data analysis, data summarization, learning

This article/section is a stub — probably a pile of halfsorted notes, is not wellchecked so may have incorrect bits. (Feel free to ignore, fix, or tell me) 