Hypotheses are testable explanations and predictions
Many people think of a hypothesis as "an educated guess" (Moriarty, 1997). Is "an educated guess" a good definition of a hypothesis?
An "educated guess" is actually not a bad definition for a hypothesis -- simply an incomplete definition.
In practice, hypotheses are not really "guesses," but hypotheses aretentative statements. We don't know if hypotheses are true or not. Therefore, one of the most important aspects of hypotheses is that we must be able to determine whether hypotheses are trueornot true: hypotheses must be testable.
For example, a testable hypothesis could be:
"If I write my paper a week before the deadline and discuss it with my instructor before revision, I will get an A on the paper."
The hypothesis is specific enough to make a testable prediction. However, the hypothesis is tentative: discussing a paper with the instructor is not a guarantee of an A (although still a good strategy to get a higher grade).
An example of a statement that is NOT testable would be:
"I was a falcon in my past life."
Because there is no way to measure anything about past lives, we cannot test a statement about past lives. Therefore, the statement cannot be a hypothesis.
DEFINITION: A useful one-sentence definition of a hypothesis is: "A tentative, specific explanation or prediction of a phenomenon or an observation that can be rejected by experimental data."
Expressing a definition using only one sentence is concise. However, the definition of a hypothesis has the problem that the sentence expresses two ideas, which can be confusing. Therefore, it is useful to analyze (break apart) the idea of a hypothesis by defining two separate terms:
DEFINITION: A "General Hypothesis" is a tentative, specific explanation of a phenomenon that can be rejected by experimental data."
DEFINITION: A "Measurable Hypothesis" is a tentative, specific prediction that can be rejected by experimental data."
Given our definitions, it will be useful to explore General and Measurable hypotheses in more detail. The section "How to test hypotheses" will explain why rejection is such an important attribute for hypotheses.