They make predictions. The scientist next uses the hypothesis to generate predictions, specific statements that can be directly and unequivocally tested. In our algae example, a researcher might predict: “If agricultural fertilizers are added to a pond, the quantity of algae in the pond will increase.” Test the predictions, scientists test predictions by gathering evidence that could potentially refute the predictions and thus disprove the hypothesis.

 

The strongest form of evidence comes from experiments. An experiment is an activity designed to test the validity of a prediction or a hypothesis. It involves manipulating variables, or conditions that can change. For example, a scientist could test the prediction linking algal growth to fertilizer by selecting two identical ponds and adding fertilizer to one of them. In this example, fertilizer input is an independent variable, a variable the scientist manipulates, whereas the quantity of algae that results is the dependent variable, a variable that depends on the fertilizer input.

 

If the two ponds are identical except for a single independent variable (fertilizer input), then any differences that arise between the ponds can be attributed to changes in the independent variable. Such an experiment is known as a controlled experiment because the scientist attempts to control for the effects of all variables except the one he or she is testing. In our example, the pond left unfertilized serves as a control, an unmanipulated point of comparison for the manipulated treatment pond.