For confidence intervals around a parameter estimate (e.g., the mean or a b in equation (2.4)) to be accurate, that estimate must come from a normal sampling distribution. The central limit theorem tells us that in large samples, the estimate will have come from a normal distribution regardless of what the sample or population data look like.
