# should i normalize dependent variable for linear regression?

If we want to perform a multiple linear regression on the dependent variable $Y$ by independent variables $X_1$,$X_2$, etc., should I normalize the $X_i$ variables only? Or should I also normalize the dependent variable $Y$?

If I normalize $Y$ , how will I interpret the predicted values? Won't the predicted values be in the normalized form? How should I denormalize them to get the exact values?

Also, which is the best normalization method, if my $X_i$ variables are a mixture of both continuous and categorical variables?