Scientific Grouping

Any number that can be measured in some way is referred to as a variable. This could be anything from temperature to height to age. A variable is basically anything that influences the outcome or result of your experiment in some way.

There are three types of variables in an experiment: independent, dependent, and controlled variables.

The variable that the experimenter has control over is referred to as an independent variable. In a nutshell, it's the variable you pick to adjust in an experiment. There are no additional variables that affect this variable.

The light color, for example, is the independent variable in the plant growth experiment. Nothing has an effect on the light color. You'll use a variety of light hues, such as green, red, and yellow. You're not using a light meter.

A dependent variable is a measurement that varies as a result of the experiment's adjustments. The name comes from the fact that this variable is dependant on other variables. The dependent variable in the plant growth experiment, for example, would be plant growth.

This may be determined by calculating how much the plant grows every two days. The rate of photosynthesis could potentially be used to determine it. Depending on the type of light you offer the plant, either of these measurements will be different.

In research, a control variable is any additional parameter that affects your experiment that you want to maintain constant across all situations.

An effect could be attributable in part to the amount of water a plant received, for example. In science investigations, a control variable is what allows you to compare other factors that may be influencing a result since you have kept other key factors constant across all of your participants.

It's crucial to remember which variable goes on which axis when graphing the results of your experiment.

On the x-axis, the independent variable is plotted. The y-axis is used to graph the dependent variable, which changes in reaction to the independent variable. Because controlled variables should not change, they are rarely graphed. They might, however, be graphed as proof that other conditions remain constant.

You could, for example, look at how the temperature varied across different situations after charting the growth in relation to light. If you observe that it varies significantly, you may need to revisit your experimental arrangement.

To help you remember which variable is the dependent and which is the independent, try putting them together in a sentence that includes the phrase "causes a change in."

Here's an illustration. It's feasible to say, "light color induces a shift in plant development." The independent variable has an effect on the dependent variable, as evidenced by this. The inverse, on the other hand, is not true. It is not viable to say that "plant growth causes a change in light color." This way, you'll know which variable is independent and which is dependent.