In the context of statistical analysis, what is the difference between Type I and Type II errors?
A) Type I error is rejecting a true null hypothesis, while Type II error is failing to reject a false null hypothesis.
B) Type I error is failing to reject a true null hypothesis, while Type II error is rejecting a false null hypothesis.
C) Type I error is related to sample size, while Type II error is related to effect size.
D) Type I error is a computational mistake, while Type II error is a logical fallacy.