Why is it compared to the value of 0.7? Also when you compare the negative value to 0.7 I'm assuming you're actually looking more at the absolute value?
Hello sir. Is it possible for the data to have 2 dependant variables? For example bowling games; the labels are won, lost, strike, spare, 1 pins, 2 pins, etc. So the dependant variables are both won and lost? Or multicollinearity only have 1 y and all the other is x?
If I want to remove the multicollinearity, which variable that I should remove? x1 or x2?
Why is it compared to the value of 0.7?
Also when you compare the negative value to 0.7 I'm assuming you're actually looking more at the absolute value?
Hello sir. Is it possible for the data to have 2 dependant variables? For example bowling games; the labels are won, lost, strike, spare, 1 pins, 2 pins, etc. So the dependant variables are both won and lost? Or multicollinearity only have 1 y and all the other is x?
Speaking about regression there is only one dependent variable.
You can have two models each with a different dependent variable
@@jskeshminder4627 noted Dr. Thank you for your respond👍
According to which rule one can assume that there is or no collinearity between independent variables? can't hear well.
You have to check for multicollinearity
Watch 2:47 - Value > 0.7,. However, there a various thresholds - read on VIF