i mean when we are using the statistic in real life how many distributions do we need to know ?
- Normal
- Normal Log
- Poisson
- t student
and how many others , i ask in case i work with statistic some day
2026-03-30 05:28:54.1774848534
how many statistical distributions in real life?
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Realistically, there is no limit. Commonly occurring 'named' distributions include uniform, normal (also called Gaussian), Bernoulli*, binomial*, Poisson*, beta, gamma (and its special cases chi-squared and exponential), Student's t, Snedecor's F.
Somewhat less commonly: Laplace, negative binomial* (and special case, geometric*), hypergeometric*, lognormal (which is not log of a normal), Weibull, Pareto, Rayleigh, etc.
These are only partial lists from memory, and in no particular order. I have put asterisks (*) after 'discrete' distributions in my list. The rest are 'continuous". Then there are many other useful distributions that do not (yet) have names.
As you may guess, mathematicians and statisticians are not shy about naming distributions they discover or use after themselves, mentors, or predecessors. (Often the name of a distribution has little to do with it's origin or history, and some names differ by country.)
If you want to learn more about any one of these distributions, look in indexes of applied probability and mathematical statistics books. Also, you can google (with care); I have found Wikipedia to be almost always accurate.