Independent and dependent variables are terms used in mathematical modeling, statistical modeling, and experimental sciences. Here are some key points about independent and dependent variables:
Independent Variable
- An independent variable is the variable that is manipulated or varied in an experimental study to explore its effects.
- It is called "independent" because it is not influenced by any other variables in the study.
- Independent variables are also called "predictor variables" or "regressors" in a statistical context.
- Some common independent variables are time, space, density, mass, fluid flow rate, and previous values of some observed value of interest.
Dependent Variable
- A dependent variable is the variable that changes as a result of the independent variable manipulation.
- It is the outcome that researchers are interested in measuring, and it "depends" on the independent variable.
- Dependent variables are also called "response variables" in statistics.
- In an experiment, any variable that can be attributed a value without attributing a value to any other variable is called an independent variable.
- The dependent variable is sometimes called the "response," the "symptoms," or the "outcome".
To determine the dependent and independent variables in a study, you need to identify what the study is measuring. The dependent variable is the variable being tested and measured in an experiment and is "dependent" on the independent variable. The independent variable is the variable being controlled in the problem, and the dependent variable is the variable that changes because of this control.
