, Volume 11, Issue 3, pp 207-233

Exact Bounds on Finite Populations of Interval Data

Rent the article at a discount

Rent now

* Final gross prices may vary according to local VAT.

Get Access


In this paper, we start research into using intervals to bound the impact of bounded measurement errors on the computation of bounds on finite population parameters (“descriptive statistics”). Specifically, we provide a feasible (quadratic time) algorithm for computing the lower bound \(\underline{\sigma^2}\) on the finite population variance function of interval data. We prove that the problem of computing the upper bound \(\bar{\sigma}^2\) is, in general, NP-hard. We provide a feasible algorithm that computes \(\bar{\sigma}^2\) under reasonable easily verifiable conditions, and provide preliminary results on computing other functions of finite populations.