Final answer:
In a hypothesis test, a Type I error occurs when we wrongly reject a true null hypothesis, which in this case means rejecting the claim that the proportion of left-handed women is less than 10% when it actually is.
Step-by-step explanation:
In the context of a hypothesis test for the claim that the proportion of left-handed women is less than 10%:
Type I error is made when we reject a true null hypothesis. In this specific case, it would mean that we incorrectly reject the claim that the proportion of left-handed women is less than 10%, even when it actually is less than 10%. Therefore, Option 1: Rejecting the claim when it is true, represents a Type I error.
It is important to note that both Type I and Type II errors are related to the concept of proportion in this hypothesis test, which involves determining whether statistical evidence supports a specific claim about a population proportion.