A type I error is a kind of fault that occurs during the hypothesis testing process when a null hypothesis is rejected, even though it is accurate 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 to trigger an outcome to the test.

This condition is denoted as "n=0." Ifâ€”when the test is conductedâ€”the result seems to indicate that the stimuli applied to the test subject cause a reaction then the null hypothesis that the stimuli do not affect the test subject will be rejected.

## False Positive 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 something other than the stimuli causes the outcome of the test, it can cause a "false positive" result where it appears the stimuli acted upon the subject, but the outcome was 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 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.