Under what circumstances should the data be normalized/standardized when building a regression model. When i asked this question to a stats major, he gave me an ambiguous answer "depends on the data".
But what does that really mean? It should either be an universal rule or a check list of sorts where if certain conditions are met then the data either should/ shouldn't be normalized.
It should either be an universal rule or a check list of sorts where if certain conditions are met then the data either should/ shouldn't be normalized.
Can you justify that? $\endgroup$