biased statistic

biased statistic

[′bī·əst stə′tis·tik]
(statistics)
A statistic whose expected value, as obtained from a random sampling, does not equal the parameter or quantity being estimated.
References in periodicals archive ?
In this paper, we study how individuals learn from potentially biased statistics using data from both a natural experiment and a survey experiment during a period (2007-15) when the government of Argentina was manipulating official inflation statistics.
To address these limitations in the observational data, we provide a simple model of Bayesian learners with potentially biased statistics and design a survey experiment to test its predictions.
The experimental data also allow us to directly test the hypothesis that there may be sophisticated learning from potentially biased statistics.
More generally, the study of biased statistics goes back to the seminal contribution by Oskar Morgenstem (1963) on measurement, accuracy, and uncertainty in economics.
The most important prediction of this model is that a Bayesian learner is not expected to ignore biased statistics, but instead rationally adjust to the perceived bias.
Rather than simply ignoring biased statistics or accepting them as unbiased, individuals can effectively adjust for the perceived bias using other available information.
They include the simple logic that "failing" schools can be turned around whether they are academies or council-maintained schools - with extra support, good leadership and teaching - whatever biased statistics the government produces for academy success rates.
We do not need to complicate the ordering process, especially with biased statistics that were never intended to be applied on an individual basis.
It makes us furious when we are forced to sit and listen to them quoting biased statistics and feeding councillors misguided information and we are not allowed to reply.
In a recent interview with Kyodo News, Kono, a House of Representatives member, said that in many conflicts he has witnessed different sides exchange opinions based on biased statistics and information.