Final answer:
A false positive in hypothesis testing indicates that the null hypothesis is true but the experimenter incorrectly rejects it, which is a Type I error.
The correct answer to the question is option 4) null hypothesis, fails to rejects.
Step-by-step explanation:
Hypothesis testing is based on probabilities, and as such, conclusions are drawn based on the evidence and the likelihood of the observed result assuming the null hypothesis is true. The probability of committing a Type I error is usually denoted by the Greek letter alpha (α).
If a result is a false positive, in reality the null hypothesis is true, but the experimenter rejects the null hypothesis. So, the correct answer is option 4) null hypothesis, rejects.
In hypothesis testing, this type of error is known as a Type I error, where the decision is to reject the null hypothesis when, in fact, the null hypothesis is true.
It is important to remember that rejecting or failing to reject a hypothesis does not prove the hypothesis true or false.