Which of the following is a reason why a researcher may design an experiment with more than two levels of an independent variable? A design with only two levels of an independent variable cannot provide much information about the exact form of the relationship between the independent and dependent variables. When there are only two levels of an independent variable, the relationship between the independent and dependent variables cannot be described with a straight line. An experiment with only two levels of one independent variable always tends to show that there is a positive relationship between the independent and dependent variables. An experimental design with only two levels of the independent variable can only detect curvilinear relationships between the independent and dependent variables.

A design with only two levels of an independent variable cannot provide much information about the exact form of the relationship between the independent and dependent variables.

Explanation:

Researchers use multiple levels of an independent variable to produce every possible combination, which is then used as a condition in the experiment. It is important not to confuse having multiple independent variables with having more than two levels of independent variable. For example, if we want to study the impact of income level of parents on the expenditure of student, we know that the independent variable here is the income level, however, we could proxy it into low income level, medium income level, and high income level. The three levels of the independent variable could be individually correlated and regressed against the dependent variable, which is the student expenditure.