However, the two tests are not completely redundant; as a result the joint probability of their rejection is less than ?.
22.
The joint probability distribution function " p ( C, T ) " represents the probability that two events occur simultaneously.
23.
After the solution attempt, the principle behind the joint probability of two independent events will be explained, using the chosen example.
24.
Teachers may then use the other examples in order to deepen the understanding of joint probabilities, for example by using worked examples.
25.
The testing sample is previously unseen by the algorithm and so represents a random sample from the joint probability distribution of x and y.
26.
The generative probabilistic model is defined through the joint probability density p ( X ^ o, x ^ m, h ) \,.
27.
If the network structure of the model is a directed acyclic graph, the model represents a factorization of the joint probability of all random variables.
28.
Moreover, the joint probability distribution of the energy values of two different microscopic configurations of the spins, \ sigma and \ sigma'factorizes:
29.
Note however that we derived the simplified expression for the conditional distribution above simply by rewriting the expression for the joint probability and removing constant factors.
30.
RDM can also incorporate probabilistic information, but rejects the view that a single joint probability distribution represents the best description of a deeply uncertain future.
