Answer:
It is measured using a measure called variance inflation factor (VIF).
Step-by-step explanation:
This is the statement that is true about multi-collinearity. Multi-collinearity is a situation that can sometimes arise when dealing with a multiple regression model. Multicollinearity refers to the occurrence of high intercorrelations among various independent variables. This can often lead to results that are skewed or misleading. The main way in which multi-collinearity can be measured is by using the variance inflation factor (IVF). This allows us to quantify the severity of multi-collinearity.
Answer:
i think it is b
Step-by-step explanation:
Answer:
11 because adjacent is basically next to and NKL is 12
Step-by-step explanation:
They gave you an eqution with variables and then they gave you numbers that all you have to do is put in
k(h-j)+h
5(5-4)+5
5(1)+5
5+5
10
