The independent and dependent variables are the two main types of variables in a science experiment. A variable is anything you can observe, measure, and record. This includes measurements, colors, sounds, presence or absence of an event, etc.
Key Takeaways: Difference Between Independent and Dependent Variables
- The independent variable is what the experimenter changes.
- The dependent variable is what the experimenter measures.
- The independent variable is the cause; the dependent variable is the effect.
- Graph the independent variable on the x-axis, and the dependent variable on the y-axis.
- Use the acronym DRY MIX to remember which variable goes where on a graph.
The independent variable is the one factor you change to test its effects on the dependent variable. In other words, the dependent variable “depends” on the independent variable. The independent variable is sometimes called the controlled variable, while the dependent variable is the experimental or responding variable. This is misleading, though. A controlled variable is kept constant to ensure a fair test, while the independent variable is the one intentionally changed.
- The independent variable is the one you control or manipulate. The dependent variable is the one that responds and that you measure.
- The independent variable is the cause, while the dependent variable is the effect.
- Graph the independent variable on the x-axis. Graph the dependent variable on the y-axis.
How to Identify the Independent and Dependent Variables
Both the independent and dependent variables may change during an experiment, but the independent variable is the one you control, while the dependent variable is one you measure in response to this change. The easiest way to tell the two variables apart is to phrase the experiment in terms of an “if-then” or “cause and effect” statement. If you change the independent variable, then you measure its effect on the dependent variable. The cause is the independent variable, while the effect is the dependent variable. For example, “Time spent studying affects grades” makes logical sense, because study time (independent variable) influences test scores (dependent variable). The reverse (“grades affect time spent studying”) does not follow the cause-and-effect logic.
Sometimes the independent variable is easy to identify. Time and age are almost always the independent variable in an experiment. You can measure them, but you can’t control any factor to change them.
Ask yourself these questions to help tell the two variables apart:
Independent Variable
- Can you control or manipulate this variable?
- Does this variable come first in time?
- Are you trying to tell whether this variable affects an outcome or answers a question?
Dependent Variable
- Does this variable depend on another variable in the experiment?
- Do you measure this variable after controlling another factor?
Independent and Dependent Variable Examples
For example, if you want to see whether changing dog food affects your pet’s weight, you can phrase the experiment as, “If I change dog food, then my dog’s weight may change.” The independent variable is the type of dog food, while the dog’s weight is the dependent variable.
In an experiment to test whether a drug is an effective pain reliever, the presence, absence, or dose of the drug is the variable you control (the independent variable), while the pain level of the patient is the dependent variable.
In an experiment to determine whether ice cube shapes determine how quickly ice cubes melt, the independent variable is the shape of the ice cube, while the time it takes to melt is the dependent variable.
If you want to see if the temperature of a classroom affects test score, the temperature is the independent variable. Test scores are the dependent variable.
| Experiment | Independent Variable | Dependent Variable |
|---|---|---|
| Type of fertilizer and plant growth | Type of fertilizer | Plant height |
| Hours of sleep and test performance | Hours of sleep | Test score |
| Temperature and reaction rate | Temperature | Reaction speed |
| Exercise and heart rate | Exercise level | Heart rate |
Graphing Independent and Dependent Variables With DRYMIX
By convention, the independent variable is plotted on the x-axis of a graph, while the dependent variable is plotted on the y-axis. Use the DRY MIX acronym to remember the variables:
D is the dependent variable
R is the variable that responds
Y is the y-axis or vertical axis
M is the manipulated or controlled variable
I is the independent variable
X is the x-axis or horizontal axis
FAQs About Independent and Dependent Variables
- Can an experiment have more than one independent variable?
Yes, but it’s harder to isolate effects. Most well-designed experiments test one independent variable at a time. - Can a variable be both independent and dependent?
Not in the same experiment. However, in different contexts, a variable might serve different roles. - What is a constant variable?
A variable that does not change during the experiment; also called a controlled variable. - Are time and age always independent variables?
Usually, yes, because you cannot manipulate them—only observe them over intervals.
References
- Carlson, Robert (2006). A Concrete Introduction to Real Analysis. CRC Press.
- Edwards, Joseph (1892). An Elementary Treatise on the Differential Calculus (2nd ed.). London: MacMillan and Co.
- Everitt, B. S. (2002). The Cambridge Dictionary of Statistics (2nd ed.). Cambridge UP. ISBN 0-521-81099-X.
- Hinkelmann, Klaus; Kempthorne, Oscar (2008). Design and Analysis of Experiments. Volume I: Introduction to Experimental Design (2nd ed.). Wiley. ISBN 978-0-471-72756-9.
- Quine, Willard V. (1960). “Variables Explained Away“. Proceedings of the American Philosophical Society. American Philosophical Society. 104 (3): 343–347.