What does dependent variable mean in science

In the context of scientific experiments, there are three different types of variables: dependent variables , independent variables , and control variables. Independent variables are the factors that you change to see how they affect the results.

Dependent variables are things that are affected by the changes that you make—the results of the tests which depend on the independent variables. Control variables are the factors that you do not change. They are kept the same for every test or measurement in order to make sure that the results can be compared fairly.

The dependent variable is the final height of the sunflower. The independent variable the factor that you change is the brand of plant food. There are a number of other factors that could impact the growth of the plant, including things like the amount of sunlight and the amount of water. To allow for a proper comparison of the results, these need to be control variables —they need to be controlled, or kept the same.

This way, you can have a greater degree of certainty that the final difference in heights the dependent variable is due to which food each sunflower received the independent variable , not differences in sunlight or water.

Science is messy. The dependent variable is the thing being impacted. Scientists are trained to be careful when setting all the variables for an experiment. Understanding the importance of variables will make you more likely to draw sound conclusions and less likely to fall for claims based on faulty science. For example, when examining suspicious statistics or experiment results, a good place to start is to ask what independent variables were involved—what was changed to get the dependent variable to change.

The term dependent variable is used in the context of formal scientific experiments, but you use the same concept all the time without thinking about it. The process of trial and error involves trying new methods of doing something until you get the results you want.

The new methods are the independent variables and the results of each attempt are the dependent variables. Every experiment has a dependent variable , regardless of what is being studied. Answer: Just like an independent variable, a dependent variable is exactly what it sounds like.

It is something that depends on other factors. For example, a test score could be a dependent variable because it could change depending on several factors such as how much you studied, how much sleep you got the night before you took the test, or even how hungry you were when you took it.

Usually when you are looking for a relationship between two things you are trying to find out what makes the dependent variable change the way it does.

Many people have trouble remembering which is the independent variable and which is the dependent variable. An easy way to remember is to insert the names of the two variables you are using in this sentence in they way that makes the most sense. Then you can figure out which is the independent variable and which is the dependent variable:. Independent variable causes a change in Dependent Variable and it isn't possible that Dependent Variable could cause a change in Independent Variable.

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. 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. For example, we might change the type of information e.