In addition, we designed an alternative strategy: the development of a Bayesian network to examine the relationship between the selected variables in probabilistic terms (via

Bayes's theorem).

In Research on Social Work Practice, Wolf-Branigin and Duke (2007) attempted to use

Bayes's theorem to compute probabilities of involvement in spiritual activities and completing a Salvation Army substance abuse treatment program.

The notation for conditional probability is needed to illustrate

Bayes's theorem. If A and I are propositions, we write a conditional probability as P(A 11), which is the probability that A is true, given that I is true.

One focus of my current research, which involves, among other things, a new proof of

Bayes's theorem, uses a calculus of variations information theoretic framework and generalisations of it, described in my works published since my 1988 American Statistician article [Zellner (1988)] with commentary by Edwin T.

Using a more general form of

Bayes's Theorem, we then use the surname lists to update the prior probabilities of membership in each of the four race/ ethnic categories with the surname list results to produce efficient, updated posterior probabilities of membership in the four groups.

* Demonstrate how

Bayes's theorem may be useful in evaluating the data in the case.

the hypotheses being that the population size is 10 and 1 million, respectively) and where the probability of the evidence (that "you" receive body number 7) is P ([e\h.sub.10]) = 0.1 and P(e\[h.sub.1M]) = 0.000001, then by

Bayes's theorem:

For in view of

Bayes's Theorem, the conditional probability of such a belief upon any evidence that is possible given one's initial beliefs, will always be equal to one.

Holder analyzes the probabilities of these two options with the use of

Bayes's theorem (described in an appendix) and concludes in his final chapter that "Theism Wins." That title is a bit too triumphal for my taste, but it does not affect the strength of the argument.