In experiments, you have to test one independent variable at a time in order to accurately understand how it impacts the dependent variable. A variable may be thought to alter the dependent or independent variables, but may not actually be the focus of the experiment. So that the variable will be kept constant or monitored to try to minimize its effect on the experiment. Such variables may be designated as either a “controlled variable”, “control variable”, or “fixed variable”.

  • Remember, the independent variable is what you control/change, and the dependent variable is what changes because of that.
  • Sometimes, even if their influence is not of direct interest, independent variables may be included for other reasons, such as to account for their potential confounding effect.
  • A variable may be thought to alter the dependent or independent variables, but may not actually be the focus of the experiment.
  • In high school she scored in the 99th percentile on the SAT and was named a National Merit Finalist.
  • Do not confuse it with a “control variable,” which is a variable that is purposely held constant so that it can’t affect the outcome of the experiment.

The variable \(x\) is the independent variable, and \(y\) is the dependent variable. Typically, you choose a value to substitute for the independent variable and then solve for the dependent variable. As you can see, this is a graph showing how the number of hours a student studies affects the score she got on an exam. From the graph, it looks like studying up to six hours helped her raise her score, but as she studied more than that her score dropped slightly. Determining cause and effect is one of the most important parts of scientific research. It’s essential to know which is the cause – the independent variable – and which is the effect – the dependent variable.

Experiment 3: Simple Machines

Suppose you want to check the height of a normal at different ages. So here the dependent variable is height, while the independent variable is the age, which is going to change on its own. Hence, here the height of the boy is shown on the y-axis, whereas x-axis indicates the age. For example, a scientist wants to see if the brightness of light has any effect on a moth being attracted to the light. How the moth reacts to the different light levels (distance to light source) would be the dependent variable.

You can apply just two levels in order to find out if an independent variable has an effect at all. You measure the math skills of all participants using a standardized test and check whether they differ based on room temperature. You vary the room temperature by making it cooler for half the participants, and warmer for the other half. For instance rent depends upon square feet of an apartment bulding. In this example rent is dependent variable which depends upon square feet which is an independent variable. The variable x is the independent variable, and y is the dependent variable.

How to Remember the Difference Between Independent and Dependent Variables

A dependent variable is a consequence of an independent variable i.e. it is variable that measures the effect of the independent variable on the test units. The dependence of the former on the latter is being examined by the statistical models. So, here in this article, we are going to discuss some important points of difference between independent and dependent variable. A dependent variable is the variable being tested and measured in a scientific experiment.

Quiz: Test Your Variable Knowledge

You want to find out how blood sugar levels are affected by drinking diet soda and regular soda, so you conduct an experiment. If you want to know more about statistics, methodology, or research bias, make sure to check out some of our other articles with explanations and examples. Based on your results, you note that the placebo and low-dose groups show little difference in blood pressure, while the high-dose group sees substantial improvements. This doesn’t really make sense (unless you can’t sleep because you are worried you failed a test, but that would be a different experiment). A marketer changes the amount of money they spend on advertisements to see how it affects total sales. While one group gets the placebo, the other group gets the medication that is intended to have therapeutic value.

What Is an Independent Variable? What Is a Dependent Variable?

Based on your findings, you can estimate the degree to which your independent variable variation drives changes in your dependent variable. You can also predict how much your dependent variable will change as a result of variation in the independent variable. You have three independent variable levels, and each group gets a different level of treatment.

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Of the two, it is always the dependent variable whose variation is being studied, by altering inputs, also known as regressors in a statistical context. In an experiment, any variable that can be attributed a value without attributing a value to any other variable is called an independent variable. Models and experiments test the effects that the independent variables have on the dependent variables.

A variable is extraneous only when it can be assumed (or shown) to influence the dependent variable. This effect is called confounding or omitted variable bias; in these situations, design changes and/or controlling for a variable statistical control is necessary. There can be multiple dependent variables for one independent variable. In a scientific experiment, the independent variables are controlled or changed whereas the dependent variables tend to be measured and tested.

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An example of a dependent variable is how tall you are at different ages. The dependent variable (height) depends on the independent variable (age). An independent variable is the variable you manipulate, control, or vary in an experimental study to explore its effects. It’s called “independent” because it’s not influenced by any other variables in the study. Independent and dependent variables are commonly taught in high school science classes.