# Dependent Variable Definition and Examples If you are interested in learning which kind of chicken produces the largest eggs, the breed is the independent variable and egg size is the dependent variable. Marsi / Getty Images

A dependent variable is the variable being tested in a scientific experiment.

The dependent variable is "dependent" on the independent variable. As the experimenter changes the independent variable, the change in the dependent variable is observed and recorded. When you take data in an experiment, the dependent variable is the one being measured.

Common Misspellings: dependant variable

## Dependent 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. A change in the independent variable (amount of light) directly causes a change in the dependent variable (moth behavior).
• You are interested in learning which kind of chicken produces the largest eggs. The size of the eggs depends on the breed of chicken, so breed is the independent variable and egg size is the dependent variable.
• You want to know whether or not stress affects heart rate. Your independent variable is the stress, while the dependent variable would be the heart rate. To perform an experiment, you would provide stress and measure the subject's heartbeat. Note that in a good experiment, you'd want to choose a stress you could control and quantify. Your choice could lead you to perform additional experiments since it might turn out the change in heart rate after exposure to a decrease in temperature 40 degrees (physical stress) might be different from the heart rate after failing a test (psychological stress). Even though your independent variable might be a number that you measure, it's one you control, so it's not "dependent".

## Distinguishing Between Dependent and Independent Variables

Sometimes it's easy to tell the two types of variables apart, but if you get confused, here are tips to help keep them straight:

• If you change one variable, which is affected? If you're studying the rate of growth of plants using different fertilizers, can you identify the variables? Start by thinking about what you are controlling and what you will be measuring. The type of fertilizer is the independent variable. The rate of growth is the dependent variable. So, to perform an experiment, you would fertilize plants with one fertilizer and measure the change in height of the plant over time, then switch fertilizers and measure the height of plants over the same span of time. You might be tempted to identify time or height as your variable, not the rate of growth (distance per time). It may help to look at your hypothesis or purpose to remember your goal.
• Write out your variables as a sentence stating cause and effect. The (independent variable) causes a change in the (dependent variable). Usually, the sentence won't make sense if you get them wrong. For example:
(Taking vitamins) affects the numbers of (birth defects). = makes sense
(Birth defects) affects the number of (vitamins). = probably not so much

## Graphing the Dependent Variable

When you graph data, the independent variable is on the x-axis, while the dependent variable is on the y-axis. You can use the DRY MIX acronym to remember this:

D - dependent variable
R - responds to change
Y - Y-axis

M - manipulated variable (one you change)
I - independent variable
X - X-axis