The correct answer is: B. relevant range of linearity
A relevant range of linearity is the range of values for the independent variable within which the relationship between the independent and dependent variables is linear. Outside of this range, the relationship may not be linear.
For example, if you are trying to predict the height of a person based on their weight, the relationship between height and weight will be linear for most people. However, there will be some people who are very tall or very short, and for these people the relationship between height and weight will not be linear.
The relevant range of linearity is important because it determines the accuracy of the predictions that you can make. If you try to make predictions outside of the relevant range, your predictions will be less accurate.
The other options are incorrect because:
- Option A, irrelevant range of linearity, is not a term that is used in statistics.
- Option C, significant range, is a term that is used in statistics, but it does not refer to the range of values for the independent variable within which the relationship between the independent and dependent variables is linear.
- Option D, insignificant range, is not a term that is used in statistics.