The two main variables in a science experiment are the independent variable and the dependent variable. Here's the definition on independent variable and a look at how it's used:

### Key Takeaways: Independent Variable

- The independent variable is the factor that you purposely change or control in order to see what effect it has.
- The variable that responds to the change in the independent variable is called the dependent variable. It depends on the independent variable.
- The independent variable is graphed on the x-axis.

### Independent Variable Definition

An independent variable is defines as the variable that is changed or controlled in a scientific experiment. It represents the cause or reason for an outcome.

Independent variables are the variables that the experimenter changes to test their dependent variable. A change in the independent variable directly causes a change in the dependent variable. The effect on the dependent variable is measured and recorded.

**Common Misspellings: **independant variable

### Independent Variable Examples

- A scientist is testing the effect of light and dark on the behavior of moths by turning a light on and off. The independent variable is the amount of light and the moth's reaction is the dependent variable.
- In a study to determine the effect of temperature on plant pigmentation, the independent variable (cause) is the temperature, while the amount of pigment or color is the dependent variable (the effect).

### Graphing the Independent Variable

When graphing data for an experiment, the independent variable is plotted on the x-axis, while the dependent variable is recorded on the y-axis. An easy way to keep the two variables straight is to use the acronym DRY MIX, which stands for:

- Dependent variable that Responds to change goes on the Y axis
- Manipulated or Independent variable goes on the X axis

### Sources

- Dodge, Y. (2003).
*The Oxford Dictionary of Statistical Terms*. OUP. ISBN 0-19-920613-9. - Everitt, B. S. (2002).
*The Cambridge Dictionary of Statistics*(2nd ed.). Cambridge UP. ISBN 0-521-81099-X. - Gujarati, Damodar N.; Porter, Dawn C. (2009). "Terminology and Notation".
*Basic Econometrics*(5th international ed.). New York: McGraw-Hill. p. 21. ISBN 978-007-127625-2.