Multicollinearity is when several independent variables are linked in some way. It can happen when attempting to study how individual independent variables contribute to the understanding of a dependent variable

The difference between multicollinearity and auto correlation is that multicollinearity is a linear relationship between 2 or more explanatory variables in a multiple regression while while auto-correlation is a type of correlation between values of a process at different points in time, as a function of the two times or of the time difference.

yes

Multicollinearity is the condition occurring when two or more of the independent variables in a regression equation are correlated.

false