Distinguish between a hypothesis and an experimental prediction. Why is it useful to test a hypothesis using many different experimental predictions?

A hypothesis is an educated guess or proposed explanation for a phenomenon, while an experimental prediction is a specific, measurable outcome expected to occur if the hypothesis is correct. Testing a hypothesis using multiple experimental predictions is crucial because it strengthens the hypothesis's validity, eliminates alternative explanations, and provides a more robust understanding of the phenomenon being studied. For example, a hypothesis stating that increasing the temperature will speed up the rate of a chemical reaction can be supported by various experimental predictions, such as doubling the temperature will result in a reaction that is twice as fast, and decreasing the temperature by 10 degrees will slow down the reaction by a specific percentage. If all these predictions are supported by experimental results, the hypothesis becomes more valid and robust.