experts. The focus of this paper is solely on how to elicit judgements about a mean and variance, and we do not consider these other issues here. Guidance on these and other aspects of elicitation can be found in [@EFSA:2014], [@Hagan:2006], [@Cooke:1991] and [@Morgan:1990].

Eliciting plausible bounds for $X_i$
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We first ask the expert to provide a lower plausible bound $L$ and an upper plausible bound $U$ for a member of the population $X_i$. She is told that $P(L<X_i<U)\simeq 1$ is assumed. Though we are assuming a normal distribution for the population, limits will still be needed when plotting density functions etc. to provide graphical feedback. Providing *two* bounds may also reduce the effect of the *anchoring and adjusting* heuristic: making a judgement by starting from an additional value, the anchor, and then making a, potentially insufficent, adjustment [@TVERSKY:1974] as the expert cannot use multiple anchors simultaneously.

Eliciting judgements about the population mean
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The expert is asked to provide at least two quantiles (denoted as $\mu_{(\alpha_1)}$ and $\mu_{(\alpha_2)}$) of her distribution of $\mu$ such that $$P (\mu \leq \mu_{(\alpha_i)}) = \alpha_i,$$ for $i=1,2$, and $0 < \alpha_1 < \alpha_2 < 1$. [@Garthwaite:2000] suggest eliciting lower and upper tertiles, 