A geometric distribution comes from a binary probability which does not have a set number of trials. It seeks to determine how many trials must be conducted before success is achieved. For example, instead of saying, "If I shoot the ball 5 times, what is my probability of success," a geometric probability would question, "How many times will I have to shoot the ball before I make a basket?"
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The complement (not compliment) of the probability of event A is 1 minus the probability of A: that is, it is the probability of A not happening or "not-A" happening.The complement (not compliment) of the probability of event A is 1 minus the probability of A: that is, it is the probability of A not happening or "not-A" happening.The complement (not compliment) of the probability of event A is 1 minus the probability of A: that is, it is the probability of A not happening or "not-A" happening.The complement (not compliment) of the probability of event A is 1 minus the probability of A: that is, it is the probability of A not happening or "not-A" happening.
Probability means Chance...in the name itself it explains.... Well, we can tell probability is an exact science only when, the data and logic and external dependent variables are exactly defined before going to calculation... If we do all the above exactly, the result will give exact chance or probability....for your need.. But in reality it is very hard to obey all the formulations of data in a series...only experts can do... I am also like to enjoy the real exact probability theory...
No 1.001 is not a probability. Probability can not be >1
Geometric probability is the probability of a random event within taking place a geometric plane. The idea of geometric probability covers a wide range of problems, but the common theme is probability as it applies to geometric shapes and objects.
Geometric probabilities are those that are either given in terms of geometric entities or can be computed in terms of geometric entities.For example, the probability that the ball tossed onto a moving roulette wheel coming up '00' could be considered a geometric probability.
Since probability is not a geometric concept, there is no definition for it in geometry.
A geometric distribution comes from a binary probability which does not have a set number of trials. It seeks to determine how many trials must be conducted before success is achieved. For example, instead of saying, "If I shoot the ball 5 times, what is my probability of success," a geometric probability would question, "How many times will I have to shoot the ball before I make a basket?"
Geometric Probability
The geometric distribution appears when you have repeated trials of a random variable with a constant probability of success. The random variable which is the count of the number of failures before the first success {0, 1, 2, 3, ...} has a geometric distribution.
In the simplest case, a geometric probability is one that is given in terms of the ratio of two areas. For example, suppose a parachutist could land anywhere on a 10 square kilometre area of open country with equal probability, and you wanted to know how probable it would be that the parachutist would land on a designated area of 2 square kilometres with that part of open country. Then the probability would be 2 / 10 = 0.2 The same principles apply in more and more difficult or complex cases, and in spaces of higher dimension. For instance, one can discuss geometric probabilities involving three-dimensional space.
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Exponential distribution is a function of probability theory and statistics. This kind of distribution deals with continuous probability distributions and is part of the continuous analogue of the geometric distribution in math.
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