Which of the following statements about large-sample, nonparametric reference limits is true?

• A. True
• B. False
• C. Only true for Gaussian data
• D. Only true for n < 40

Answer: (A)

Nonparametric reference limits rely on order statistics—the percentile cutoffs of the data—without assuming any specific distribution. In a large sample, the empirical distribution function converges to the true distribution, so the estimated percentiles (the reference limits) converge to the population percentiles. This makes the reference limits valid regardless of the underlying distribution and independent of a small-sample threshold like n < 40. In other words, you can reliably derive a central reference interval from data alone as the sample size grows, which is why this statement is true. The idea that it only applies to Gaussian data or only to small samples doesn’t fit with the distribution-free, asymptotic nature of nonparametric reference limits.