What are some common misconceptions about linear regression?

What are some common misconceptions about linear regression?

One common misconception is that linear regression can only be used for linear relationships, but it can also model non-linear relationships with transformations.

Can linear regression handle outliers?

Outliers can significantly affect linear regression results, but there are techniques to mitigate their impact, like robust regression.

Is linear regression the best method for all types of data?

Not necessarily. While linear regression is powerful, it may not be the best choice for all datasets, especially those with complex relationships.

What assumptions does linear regression make?

Linear regression assumes linearity, independence, homoscedasticity, and normality of residuals among other things.

How can I check if my linear regression model is valid?

You can check the validity of your model by analyzing residual plots, checking for multicollinearity, and using metrics like R-squared.