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. 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. 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.
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. 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. The dependent variable is your effect. When it comes to an experiment, dependent variables are what you change or measure.
It is dependent on your other variables. For example:. When doing a science experiment, some variables need to remain constant. These are your control variables. By keeping a variable constant, you ensure your results remain accurate. To help you understand this concept, look at our examples. While the big three are typically what you think about when it comes to an experiment, they are not the only variables.
However, the other variables that can affect a scientific experiment are a bit harder to explain. When it comes to your science experiment, there are a lot of variables to think about. Dive more into fun science topics by looking at genetic engineering and genotypes. All rights reserved. Student performing science experiment with variables. Different Types of Variables in Science As a budding scientist, you want to learn about the world around you.
Independent Variable In an experiment, you need some type of control. Possible dependent variables include: number of beans, weight of the plant, leaf surface area, time to maturation, height of stem. Independent -- is what is varied during the experiment; it is what the investigator thinks will affect the dependent variable.
In our coffee bean example, possible independent variables include: amount of fertilizer, type of fertilizer, temperature, amount of H 2 O, day length, all of these may affect the number of beans, weight of the plant, leaf area, etc.
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