When conducting studies and experiments, researchers pay attention to constants and variables to draw conclusions. Constants are the factors that do not change throughout the experiment, and variables are the factors that vary or have the potential to vary. While there are many different kinds of variables, the two most commonly discussed are the dependent and independent variables.
Other People Are Reading
What Is a Dependent Variable?
The dependent variable is the factor that receives the stimulus. Researchers measure dependent variables to explore the potential effects of the stimulus, because the aptly named dependent variable is dependent upon the stimulus to be changed. For example, in a study on the relationship between the length of a bicycle ride and the riders' heart rate, the dependent variable is the heart rate, which the length of the bicycle ride may affect.
What Is an Independent Variable?
The independent variable is the factor altered or varied to give various amounts of the stimulus. The experiment does not change the independent variable. If the researchers manipulate the variable, it is an active variable. In the aforementioned example, bicycle ride length is the active variable, because it can be changed. If the variable is an attribute variable, the researchers cannot manipulate the variable, but something is affecting the amount of stimulus. For example, in studying age versus heart rate, age is the attribute variable, because it affects the dependent variable without being manipulated.
Passive vs. Active
Some researchers observe what changes occur while they are passive to determine the dependent variable. In these cases, researchers merely record the measurements and results of the dependent variable without interference. Conversely, the independent variable is thought to be the variable acted upon. Active independent variables require researchers to act, such as adjusting a temperature or dose. For attribute variables, researchers have to find a study group that embodies the different characteristics of the study, but once the experiment or study begins, the researcher is passive.
Cause and Effect
Sometimes the dependent and independent variables are cause and effect. For example, a study looking at the number of cookies sold versus the amount of money earned can conclude the independent variable of the number of cookies causes the dependent variable, the amount of money earned. However, correlation is not proof of causation. In the example study of bicycle ride length versus the riders' heart rate, the length of the ride may appear to cause heart rates to increase, but the riders' age, health or technique might also cause the change in the dependent variable.
- 20 of the funniest online reviews ever
- 14 Biggest lies people tell in online dating sites
- Hilarious things Google thinks you're trying to search for