Hello I want to ask you, before to making a regression should we understand which distribution follow the datas?

Let's take an example: if the data have a poisson distribution, then I will run a Poisson regression?

If the data follow a gaussian then one should use the linear regression?

I don't understand when to use linear regression and when to use Poisson regression. Any real use of case example?

I leave you an example: In this post this authot uses the Poisson regression to build a model based on average goal made by 2 footbal teams Home and Away

https://dashee87.github.io/data science/football/r/predicting-football-results-with-statistical-modelling/

I don't get why he USED POISSON regression, instead of linear regression.... is it because the data followed a Poisson distribution in the first place?

Let's take an example: if the data have a poisson distribution, then I will run a Poisson regression?

If the data follow a gaussian then one should use the linear regression?

I don't understand when to use linear regression and when to use Poisson regression. Any real use of case example?

I leave you an example: In this post this authot uses the Poisson regression to build a model based on average goal made by 2 footbal teams Home and Away

https://dashee87.github.io/data science/football/r/predicting-football-results-with-statistical-modelling/

I don't get why he USED POISSON regression, instead of linear regression.... is it because the data followed a Poisson distribution in the first place?

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