Final answer:
The independent variable in an experiment is the factor that is changed or manipulated by the researcher, while the dependent variable is the factor that is measured to see the effects of the independent variable. Control variables are kept constant to ensure a fair test, and typically there should be only one dependent variable to measure the specific effect of the independent variable.
Step-by-step explanation:
In an experiment, the independent variable is the factor that is changed or manipulated by the researcher. The dependent variable, on the other hand, is the factor that is being measured or observed to see the effect of the independent variable.
An example of a simple experimental question might be: Does the amount of sunlight affect the growth of plants?
In this case, the independent variable would be the amount of sunlight the plants receive, as this is what the experimenter can vary. The dependent variable would be the growth of the plants, which is what the experimenter is measuring to see if there is an effect from the varying levels of sunlight.
When conducting an experiment, ideally, you want to have one dependent variable, so you can specifically measure the effects of the independent variable. Control variables are other factors in the experiment that are kept constant to prevent them from affecting the dependent variable.
Control variables are important because they help ensure that any changes in the dependent variable are likely due to the manipulation of the independent variable, rather than some other factor.
In the example of a scientist growing bacteria on gel, the independent variable would be the type of gel (A or B), and the dependent variable would be the number of bacteria present after 24 hours.
An experiment like the plant growth scenario must also account for control variables such as type of plant, soil quality, water, and other conditions that could affect plant growth.