What does the principle of parsimony suggest?

A) A simple model with fewer independent variables may not produce an effective result.
B) The fewest number of explanatory variables that explain the independent variable need to be included in the model.
C) Good regression models are often based on sound technical analysis.
D) To avoid the problem of multicollinearity,the number of independent variables need to be sufficiently high.

Parsimony Principle

The Parsimony Principle, often used in scientific research, is the idea that the simplest explanation is usually correct, encouraging minimal assumptions.

Independent Variables

Variables in a statistical model that are manipulated or categorised to determine their effect on dependent variables.

Multicollinearity

A statistical phenomenon where two or more predictor variables in a multiple regression model are highly correlated, potentially distorting estimates and making the model unreliable.