Null hypothesis

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In statistics, a null hypothesis is what you expect to happen before you run an experiment. The idea is that if the results don't reject the null hypothesis, then you aren't finding anything new or surprising. The most common null hypothesis is the "no-change" or "no-difference" hypothesis. For example, if you're testing whether a thing works, and starting with the null hypothesis that it won't work. The term was first used by Ronald Fisher in his book The design of experiments.[1]

Every experiment has a null hypothesis.

• If you do an experiment to see if a medicine works, the null hypothesis is that it doesn't work.
• If you do an experiment to see if people like chocolate or vanilla ice cream better, the null hypothesis is that people like them equally.
• If you do an experiment to see if either boys or girls can play piano better, the null hypothesis is that boys and girls are equally good at playing the piano.

The opposite of a null hypothesis is an alternative hypothesis. Some examples of alternative hypotheses are:

• This medicine makes people healthier.
• People like chocolate ice cream better than vanilla.
• Girls are better at playing the piano than boys.

References

1. Oxford English Dictionary: "null hypothesis," first usage: 1935 R.A. Fisher, The Design of Experiments ii. 19, "We may speak of this hypothesis as the 'null hypothesis', and it should be noted that the null hypothesis is never proved or established, but is possibly disproved, in the course of experimentation".