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Linear regression has assumptions. How does bagging affect model assumptions for linear regression?

Also, should you build a bagged linear model with correlated and statistically significant variables only? Does it matter if uncorrelated or statistically insignificant variables are used to build a bagged linear model?

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linear regression has model assumptions. how does bagging effect model assumptions for linear regression?

The bagging procedures do not affect the model assumptions of linear regression. Bagging is a technique to reduce the variance of the model you use to bag (which in the case of linear regression is not super useful since it is a high bias low variance method to begin with).

also should you build a bagged linear model with correlated and statistically significant variables only?

No. Variable selection via p values is fraught with problems, as I and others have written about previously elsewhere on this site.

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