For a distribution with unknown parameters, a direct approach to prediction is to estimate the parameters and then use the associated quantile function – for example, one could use the sample mean formula_8 as estimate for "μ" and the sample variance "s"2 as an estimate for "σ"2. Note that there are two natural choices for "s"2 here – dividing by formula_9 yields an unbiased estimate, while dividing by "n" yields the maximum likelihood estimator, and either might be used. One then uses the quantile function with these estimated parameters formula_10 to give a prediction interval.