Solution:Multiple regression is a statistical technique that predicts the value of one dependent variable based on the values of one or multiple independent variables.
It is particularly useful when the dependent variable is measured on a quantitative scale, meaning it can take on a wide range of continuous values.
In this method, the relationship between the dependent variable and independent variables is represented by an equation, which can help in understanding how specific changes in the independent variables might affect the dependent variable.
When we have a binary dependent variable, it is technically logistic regression that's used. However, logistic regression is a type of multiple regression adapted for a binary outcome.
Therefore, while it's more accurate to refer to "logistic regression" for binary outcomes, it is still a form of multiple regression.
So, while A is the most straightforward answer, B is also correct if you're interpreting "multiple regression" to encompass its various forms, including logistic regression.