Final answer:
When the true value of μ = -3.1, there is a probability of making a Type I error, which is equal to the significance level (in this case, 10%).
Step-by-step explanation:
When the true value of μ = -3.1, there is a probability of making a wrong decision known as the Type I error. In this case, the Type I error refers to rejecting the null hypothesis (H0: μ = -3.8) when it is actually true.
The probability of making a Type I error is equal to the significance level (denoted as α). Since the test was designed with a level of 10%, the probability of making a Type I error is 10% or 0.10.