What is a 'Type I Error'
A type I error is a kind of error that occurs during the hypothesis testing process when a null hypothesis is rejected even though it is true and should not be rejected. In hypothesis testing, a null hypothesis is established before the onset of a test. In some cases, the null hypothesis assumes the absence of a cause and effect relationship between the item being tested and the stimuli being applied to the test subject in order to trigger an outcome to the test. This is denoted as "n=0." If, when the test is conducted, the result seems to indicate that the stimuli applied to the test subject causes a reaction then the null hypothesis that the stimuli has no effect on the test subject will be rejected.
BREAKING DOWN 'Type I Error'
Sometimes, rejecting the null hypothesis that there is no relationship between the test subject, the stimuli and the outcome can be incorrect. If the outcome of the test is caused by something other than the stimuli, it can cause a "false positive" outcome where it appears the stimuli acted upon the subject, but the outcome was actually caused by chance. This "false positive," leading to an incorrect rejection of the null hypothesis, is called a type I error. A type I error rejects an idea that should not have been rejected.
Example of a Type I Error
For example, let's look at the trail of an accused criminal. The null hypothesis is that the person is innocent, while the alternative is guilty. A Type I error in this case would mean that the person is not found innocent and is sent to jail, despite actually being innocent.
In medical testing, a type I error would cause the appearance that a treatment for a disease has the effect of reducing the severity of the disease when in fact it does not. When a new medicine is being tested the null hypothesis will be that the medicine does not affect the progression of the disease. Let's say a lab is researching a new cancer drug. Their null hypothesis might be that the drug does not affect the growth rate of cancer cells.
After applying the drug to the cancer cells, the cancer cells stop growing. This would cause the researchers to reject their null hypothesis that the drug would have no effect. If the drug actually caused the growth stoppage, the conclusion to reject the null, in this case, would be correct. However, if something else during the test caused the growth stoppage instead of the administered drug, this would be an example of an incorrect rejection of the null hypothesis, i.e., a type I error.

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