Final answer:
It is generally better to estimate a smaller age range with tight bounds when dealing with age estimation in scientific fields like paleodemography, to achieve more precise and informative results that can lead to a better understanding of morbidity and mortality profiles.
Step-by-step explanation:
Estimating Age Range in Paleodemography
When estimating an age range in scientific disciplines like paleodemography, determining whether it is better to estimate a bigger or smaller age range involves several factors. Traditional age-estimation methods often led to the underestimation of older ages, so an unbiased method such as the transition analysis described by Boldsen et al. (2002) can provide point estimates of age with corresponding 95% confidence intervals, offering greater precision than broad intervals. A smaller age range with tight bounds is often preferred, as it provides a more specific and informative age estimate.
For instance, traditional methods may not differentiate well between a fifty-year-old and a ninety-year-old, missing critical differences in morbidity and mortality profiles. Therefore, in any scientific analytics or paleodemographic research, it's essential to use techniques that minimize bias, such as models that require fewer parameters or semiparametric methods for estimation.
Moreover, it's crucial to verify the sensibility of the results and to adjust the estimates accordingly. The aim is not precision to several significant figures but rather obtaining an estimate that is within a reasonable range, or 'the ballpark figure.' Checking against known or easily verifiable quantities is vital to ensure that an estimate is reasonable. In cases of uncertainty, additional data might be gathered to inform more accurate estimates.