A type 1 error is formally defined as being where the null hypothesis (which is that there is no difference between the groups) was falsely rejected. In practice this means that the study claims to find a difference that does not really exist, i.e. the result is a statistical fluke.
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| Fig 1: Type 1 and Type 2 error |
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| Fig 2: Type 1 and Type 2 error |
The conventional cut-off for significance is P=0.05, or a 1-in-20 chance. Hence if 20 trials were conducted, you would expect to get one that was ‘positive’ by chance alone.
Source:
Fig 1,
Fig 2,
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