Erratum to: Using Bayes’ rule in diagnostic testing: a graphical explanation

Bayes and diagnostic testing.

Interpretation of the result of a diagnostic test depends not only on the actual test result(s) but also on information external to this result, namely the test's sensitivity and specificity. This external information (also called prior information) must be combined with the data to yield the so-called updated, posterior estimates of the true prevalence and the test characteristics. The Bayesia...

Diagnostic testing: Model estimation and decision support using graphical models

Many agricultural decision problems can be treated within the framework of diagnostic testing. Observations are made sequentially in to order to classify a production unit as normal/unnormal, diseased/healthy etc. The decision problem is to find the optimal classification depending on the observations. The framework is well established and optimal use of such diagnostic testing schemes require ...

Bayes theorem. Diagnostic testing for tuberculosis in children.

Graphical Explanation in Belief Networks

Belief networks provide an important bridge between statistical modeling and expert systems. In this paper we present methods for visualizing probabilistic “evidence flows” in belief networks, thereby enabling belief networks to explain their behavior. Building on earlier research on explanation in expert systems, we present a hierarchy of explanations, ranging from simple colorings to detailed...

Teaching Bayes ' Rule : A Data

There is a current emphasis on making the introductory statistics class more dataoriented. Data distributions are used to motivate probability distributions, such as the normal, and sampling distributions. However, di culties remain in communicating the basic tenets of traditional statistical procedures such as con dence intervals and hypothesis tests. It is shown that skills in understanding r...