Understanding Variables

Independent variables are the variables that are manipulated or changed by the researcher in an experiment. They are also known as the input variables or the cause variables because they are the factors that cause changes to the dependent variable.

For example, if you were investigating the effect of temperature on the rate of photosynthesis in plants, temperature would be the independent variable. You would manipulate the temperature to see how it affects the rate of photosynthesis.

It is essential to note that an experiment should have only one independent variable. This is because if you change more than one variable, you will not know which variable caused the change in the dependent variable. Therefore, by controlling the independent variable, you can determine the effect of that variable on the dependent variable.

Thyme will often refer to independent variables as eXplanatory variables because you always graph it on the X-axis.

Dependent variables are the variables that are affected by the independent or explanatory variable in an experiment; they depend on the treatment. They are also known as the outcome variables or the effect variables. The dependent variable is what you measure or observe to determine the effect of the independent variable.

For example, in the temperature and photosynthesis experiment, the dependent variable would be the rate of photosynthesis, which is dependent on changes in temperature.

It is crucial to keep the dependent variable measuring methods consistent during an experiment to ensure that any changes observed are indeed a result of changes in the independent variable. Additionally, the dependent variable should be measurable and quantitative, meaning that it can be expressed in numerical values.

Dependent variables are always graphed on the Y-axis.

Controlled variables are the variables that are kept constant during an experiment to ensure that they do not affect the outcomes. These variables are also known as constant variables or the controlled factors; you control them and ensure for consistency. The purpose of controlling these variables is to ensure that any changes observed in the dependent variable are indeed due to changes in the independent variable and not due to other factors that were not adequately regulated.

For example, in the temperature and photosynthesis experiment, the controlled variables would include factors such as the type of plant, the amount of light, the type of light bulb, the time of year, the pH of the soil, the amount of water, and the amount of carbon dioxide. Because these are not variables we are testing for, we should do our best to keep them consistent across all treatment groups. By keeping these variables constant, you can ensure that any changes in the rate of photosynthesis are due to changes in temperature and not due to these other things that could affect photosynthesis.