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Null Hypothesis in Statistics: What is it?

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Null Hypothesis: Overview

The null hypothesis, H0 is the commonly accepted fact; it is the opposite of the alternate hypothesis. Researchers work to reject, nullify or disprove the null hypothesis. Researchers come up with an alternate hypothesis, one that they think explains a phenomenon, and then work to reject the null hypothesis.

Why is it Called the Null Hypothesis?

The word “null” in this context means that it’s a commonly accepted fact that researchers work to nullify. It doesn’t mean that the statement is null itself! (Perhaps the term should be called the “nullifiable hypothesis” as that might cause less confusion).

Why Do I need to Test it? Why not just prove an alternate one?

The short answer is, as a scientist, you are required to; It’s part of the scientific process. Science uses a battery of processes to prove or disprove theories, making sure than any new hypothesis has no flaws. Including both a null and an alternate hypothesis is one safeguard to ensure your research isn’t flawed. Not including the null hypothesis in your research is considered very bad practice by the scientific community. If you set out to prove an alternate hypothesis without considering the null hypothesis, you are likely setting yourself up for failure. At a minimum, your experiment will likely not be taken seriously.

Example of the Null Hypothesis

Not so long ago, people believed that the world was flat.
null hypothesis
Null hypothesis, H0: The world is flat.
Alternate hypothesis: The world is round.
Several scientists, including Copernicus, set out to disprove the null hypothesis. This eventually led to the rejection of the null hypothesis and the acceptance of the alternate. Most people accepted it — the ones that didn’t created the Flat Earth Society!. What would have happened if Copernicus had not disproved the null hypothesis and merely proved the alternate? No one would have listened to him. In order to change people’s thinking, he first had to prove that their thinking was wrong.

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