What are the various assumptions considered for running a multiple regression model? Are these assumptions different from the ones considered under simple regression model?

In both simple and multiple regression models, several assumptions are crucial for ensuring the validity and reliability of the results. While many of these assumptions are similar, their implications in multiple regression models are more complex due to the involvement of multiple predictors.

1. Linearity: This assumption posits that the relationship between the dependent variable and each independent variable is linear. In simple __________ __________ __________ _____ ____ _________.
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