Chances are you’ve heard of the phrase “constant variable” in science before. But what does it actually mean?
A constant variable, sometimes known as a control variable, is something you keep the same during an experiment.
Control variables help researchers better understand the effect independent variables have in research, producing more accurate results and allowing for comparison between elements, compounds, and other experiments.
In the real world, this could help us understand the best type of fuels, dual-ion batteries, and other, perhaps more recent innovations – which, by the way, are super exciting!
Anyways, this blog post will explain more about the constant variable in science, including a few examples, why these are important, and more essential details.
What is an example of a constant variable in science?
There are many different control variables in chemistry, and in science as a whole. However, common constant variables you may use in an experiment include:
- Experiment duration
- Sample volume
- The technique of the experiment
- Chemical purity
Essentially, anything that you keep the same between two or more experiments is something you control. These are just a few examples, but there are many more out there, all of which help us better understand the effect of different chemicals and their subsequent reactions.
Why are these important?
Using constant variables in science increases the validity and accuracy of an experiment or study. It helps you develop a correlation between variables of interest, too.
Without control variables, say, for instance, using different volumes of water for each experiment, it would be difficult to draw conclusive and valid results. Therefore, by choosing control variables and keeping these constant, you gain internal validity. Which, as we all know, is essential within any area of science, especially chemistry.
Remove the control variables, and you basically have no experiment…
What are a few other scientific variables?
Alongside constant variables, there are also independent and dependent variables.
Independent variables are altered by the scientist, for example, the choice of chemical to add to another substance. On the other hand, the dependent variable is observed closely and measured in the experiment. For example, this could be the volume of water evaporated or perhaps the amount of salt that dissolved.
You need two variables to have an experiment; otherwise, it’s difficult to draw a conclusion, i.e. what is the purpose of the experiment? Also, having multiple variables ensures things are repeatable, allowing you to measure the outcome of different experiments, whether the reaction between different chemicals or substances or searching for better fuel alternatives.
In an experiment investigating the effect of temperature on plant growth, the independent variable would be the temperature, the dependant variable would be what is measured, in this instance, plant height, and the control variables could include water, soil, and source of light.
Related: 4 Fun chemistry facts you didn’t know.
Control groups vs. control variables
Often, control groups and control variables become confused, too. However, these are two completely different things but follow a similar concept.
Control groups are typically a part of a study involving participants, which is not to do with chemistry.
For example, a study investigating the effect of a new painkiller would have two groups: the test group and the control group. The test group is given the new drug while the control group is either given no medication, a similar drug, or a placebo.
Control groups are important to ensure true experiments, avoiding result manipulation, and seeing whether or not the new medication (or other innovation) works correctly.
Constant variables in science, especially chemistry, are very important. Without these variables, it would be difficult to draw conclusions, we would lack internal validity, and any results that were obtained would have a certain uncertainty about them.
But these control variables are only half the battle – you also need independent and dependent variables to allow for a proper, valid experiment that contains valid and conclusive results.
In an experiment you conduct, look to have all three of these variables, using your control variables carefully to create experiments that are repeatable. Otherwise, the results will lack internal validity, and your experiment will lack ground