I'm not sure this question is well-worded. What is meant by "if the decision in part a is in error"? No decision or inference is mentioned, so we can't be sure of the question's intent.
However, the topic being questioned is clear, i.e. the difference between a Type I and Type II error. A Type I is the rejection of the null hypothesis when it was actually true, i.e. "declaring" a difference which in fact does not exist. A Type II error is the failure to reject the null hypothesis when it was false, i.e. "missing" a real difference. Being gullible means making more Type I errors, and being skeptical means making more Type II errors.
Now back to the ambiguous question. It might mean to say "since the p value was 0.05 the null hypothesis was rejected; if that rejection was in error then what type of error was it, I or II?" Untangling that means that there is no
real difference and the null hypothesis is true but was rejected by the investigator who incorrectly concluded that there was a difference. Which type of error is that?
However, the p value being 0.05 does not automatically imply that the investigator would reject the null hypothesis, hence the question is unclear.