In science, a variable is any factor, trait, or condition that can exist in differing amounts or types.
Scientists try to figure out how the natural world works.To do this they use experiments to search for cause and effect relationships. Cause and effect relationships explain why things happen and allow you to reliably predict the outcomes of an action. Scientists use the scientific method to design an experiment so that they can observe or measure if changes to one thing cause something else to vary in a repeatable way.
These factors that change in a scientific experiment are variables.
A properly designed experiment usually has three kinds of variables: independent, dependent, and controlled.
What is an Independent Variable?
The independent variable is the one that is changed by the scientist. Why just one? Well, if you changed more than one variable it would be hard to figure out which change is causing what you observe. For example, what if our scientific question was: "How does the size of a dog affect how much food it eats?"; then, during your feeding experiments you changed both the size of the dog and the time of day the dogs were fed. The data might get a bit confusing— did the larger dog eat less food than the smaller dog because of his size or because it was the middle of the day and dogs prefer to eat more in the morning?
Sometimes it is impossible to just change one variable, and in those cases, scientists rely on more-complicated mathematical analysis and additional experiments to try to figure out what is going on. Older students are invited to read more about that in our Experimental Design for Advanced Science Projects page. To be clear though, for a science fair, it is usually wise to have only one independent variable at a time. If you are new to doing science projects and want to know the effect of changing multiple variables, do multiple tests where you focus on one independent variable at a time.
What is a Dependent Variable?
The dependent variables are the things that the scientist focuses his or her observations on to see how they respond to the change made to the independent variable. In our dog example, the dependent variable is how much the dogs eat. This is what we are observing and measuring. It is called the "dependent" variable because we are trying to figure out whether its value depends on the value of the independent variable. If there is a direct link between the two types of variables (independent and dependent) then you may be uncovering a cause and effect relationship. The number of dependent variables in an experiment varies, but there can be more than one.
What is a Control Variable?
Experiments also have controlled variables. Controlled variables are quantities that a scientist wants to remain constant, and she or he must observe them as carefully as the dependent variables. For example, in the dog experiment example, you would need to control how hungry the dogs are at the start of the experiment, the type of food you are feeding them, and whether the food was a type that they liked. Why? If you did not, then other explanations could be given for differences you observe in how much they eat. For instance, maybe the little dog eats more because it is hungrier that day, maybe the big dog does not like the dog food offered, or maybe all dogs will eat more wet dog food than dry dog food. So, you should keep all the other variables the same (you control them) so that you can see only the effect of the one variable (the independent variable) that you are trying to test. Similar to our example, most experiments have more than one controlled variable. Some people refer to controlled variables as "constant variables."
In the best experiments, the scientist must be able to measure the values for each variable. Weight or mass is an example of a variable that is very easy to measure. However, imagine trying to do an experiment where one of the variables is love. There is no such thing as a "love-meter." You might have a belief that someone is in love, but you cannot really be sure, and you would probably have friends that do not agree with you. So, love is not measurable in a scientific sense; therefore, it would be a poor variable to use in an experiment.
In some experiments, time is what causes the dependent variable to change. The scientist simply starts the process, then observes and records data at regular intervals.
When a scientist performs a test or survey on different groups of people or things, those groups define the independent variable. For example:
Sometimes a variable simply represents an either/or (binary) condition. For example, something might be either present or not present during an experiment.
By Dr. Saul McLeod, updated 2019
Variables are given a special name that only applies to experimental investigations. One is called the dependent variable and the other the independent variable.
The independent variable is the variable the experimenter manipulates or changes, and is assumed to have a direct effect on the dependent variable. For example, allocating participants to either drug or placebo conditions (independent variable) in order to measure any changes in the intensity of their anxiety (dependent variable).
In a well-designed experimental study, the independent variable is the only important difference between the experimental (e.g. treatment) and control (e.g. placebo) groups.
The dependent variable is the variable being tested and measured in an experiment, and is 'dependent' on the independent variable. An example of a dependent variable is depression symptoms, which depends on the independent variable (type of therapy).
In an experiment, the researcher is looking for the possible effect on the dependent variable that might be caused by changing the independent variable.
Examples of Independent and Dependent Variables in Experiments
For example, we might change the type of information (e.g. organized or random) given to participants to see what effect this might have on the amount of information remembered.
In this particular example the type of information is the independent variable (because it changes) and the amount of information remembered is the dependent variable (because this is being measured).
Activity
For the following hypotheses name the IV and the DV.
1. Lack of sleep significantly affects learning in 10-year-old boys.IV............................................................DV...........................................................
2. Social class has a significant effect on IQ scores.IV............................................................
DV.......................................................…
3. Stressful experiences significantly increase the likelihood of headaches.
IV............................................................
DV...........................................................
4. Time of day has a significant effect on alertness.
IV............................................................
DV...........................................................
Operationalizing Variables
What are Independent and Dependent Variables?
Operational variables (or operationalizing definitions) refer to how you will define and measure a specific variable as it is used in your study. This enables another psychologist to replicate your research and is essential in establishing reliability (achieving consistency in the results).
For example, if we are concerned with the effect of media violence on aggression, then we need to be very clear what we mean by the different terms. In this case, we must state what we mean by the terms “media violence” and “aggression” as we will study them.
Therefore, you could state that “media violence” is operationally defined (in your experiment) as ‘exposure to a 15 minute film showing scenes of physical assault’; “aggression” is operationally defined as ‘levels of electrical shocks administered to a second ‘participant’ in another room’.
In another example, the hypothesis “Young participants will have significantly better memories than older participants” is not operationalized. How do we define "young", “old” or "memory"? "Participants aged between 16 - 30 will recall significantly more nouns from a list if twenty than participants aged between 55 - 70" is operationalized.
The key point here is that we have made it absolutely clear what we mean by the terms as they were studied and measured in our experiment. If we didn’t do this then it would be very difficult (if not impossible) to compare the findings of different studies into the same behavior.
Operationalization has the great advantage that it generally provides a clear and objective definition of even complex variables. It also makes it easier for other researchers to replicate a study and check for reliability.
Activity
For the following hypotheses name the IV and the DV and operationalise both variables.
1. Women are more attracted to men without earrings than men with earrings.
I.V._____________________________________________________________D.V. ____________________________________________________________
Operational definitions:
I.V. ____________________________________________________________
D.V. ____________________________________________________________
2. People learn more when they study in a quiet versus noisy place.
I.V. _________________________________________________________
D.V. ___________________________________________________________
Operational definitions:
I.V. ____________________________________________________________
D.V. ____________________________________________________________
3. People who exercise regularly sleep better at night.
I.V._____________________________________________________________D.V. ____________________________________________________________
Operational definitions:
I.V. ____________________________________________________________
D.V. ____________________________________________________________
How to reference this article:
McLeod, S. A. (2019, August 01). What are independent and dependent variables. Simply Psychology. www.simplypsychology.org/variables.html
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