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In probability theory, the chain rule [1] (also called the general product rule [2] [3]) describes how to calculate the probability of the intersection of, not necessarily independent, events or the joint distribution of random variables respectively, using conditional probabilities.
To solve such a problem, we first compute the probability that the needle crosses no lines, and then we take its complement. We compute this first probability by determining the volume of the domain where the needle crosses no lines and then divide that by the volume of all possibilities, V. We can easily see that V = πab.
Let X be a Riemann surface.Then the intersection number of two closed curves on X has a simple definition in terms of an integral. For every closed curve c on X (i.e., smooth function :), we can associate a differential form of compact support, the Poincaré dual of c, with the property that integrals along c can be calculated by integrals over X:
This probability problem seems so simple ... but can you actually solve it? Hint: You might want to use Google Earth.
The conditional probability can be found by the quotient of the probability of the joint intersection of events A and B, that is, (), the probability at which A and B occur together, and the probability of B: [2] [6] [7] = ().
The double-counted elements are those in the intersection of the two sets and the count is corrected by subtracting the size of the intersection. The inclusion-exclusion principle, being a generalization of the two-set case, is perhaps more clearly seen in the case of three sets, which for the sets A , B and C is given by
The Shamos–Hoey algorithm [1] applies this principle to solve the line segment intersection detection problem, as stated above, of determining whether or not a set of line segments has an intersection; the Bentley–Ottmann algorithm works by the same principle to list all intersections in logarithmic time per intersection.
The P versus NP problem is a major unsolved problem in theoretical computer science.Informally, it asks whether every problem whose solution can be quickly verified can also be quickly solved.