Multiple Linear Regression_1

[sourena]

it's ok, honestly, i wanted to write a mlr for 4featurtes, which contain 288 rows and 450columns, I wanted to see that whether I can use this formula: lm(y~x1+x2+x3+x4, data=df) or not?

[startz]

Assuming that df has columns named y, x1, x2, x3, and x4 that should be fine.

[sourena]

thank you ever so much
is there any pamphlet here that I can take some info about linear regressions?

[startz]

There are probably an infinite number of resources to learn about multiple regressions. Here's one (of many) that is specific to R: Multiple Linear Regression in R - Articles - STHDA

[sourena]

thank you ever so much @startz for your all help

[Bugs]

I would be more comfortable if there was consistency in terminology. "Features" is a machine learning term while dependent and independent variable are terms more common in statistics. In a machine learning approach, one often breaks the data into training, testing, and validation subsets. In classical statistics I need to assess if the model conforms to some basic assumptions. Asking questions about multiple regression and providing data on two variables is also concerning. Finally having a multiple regression of 4 independent variables in a dataset with 450 columns feels like there are other questions that should be asked/answered first.

[sourena]

yes, exactly but as the data sets are not covered here, it is quite bit hard for me to tell my question succinctly. by the way, thank you ever so much.