The correct answer is D. multi-collinearity.
Multicollinearity is a statistical phenomenon in which two or more independent variables in a regression model are highly correlated. This can cause problems in the model, such as inaccurate estimates of the coefficients and standard errors.
There are a few ways to deal with multicollinearity. One way is to remove one of the correlated variables from the model. Another way is to use a technique called ridge regression, which can help to reduce the effects of multicollinearity.
Price linearity is a situation in which the price of a product is directly proportional to its quantity. Cost linearity is a situation in which the cost of producing a product is directly proportional to its quantity. Division linearity is a situation in which the division of two numbers is equal to the quotient of their reciprocals.
These three concepts are not related to multicollinearity.