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Not sure about only two requirements. I would say all of the following:
- there is a finite (or countably infinite) number of mutually exclusive outcomes possible,
- the probability of each outcome is a number between 0 and 1,
- the sum of the probabilities over all possible outcomes is 1.
The Poisson distribution, for example, is countably infinite.
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What is the difference between a discrete and a continuous distribution?
A simple continuous distribution can take any value between two other values whereas a discrete distribution cannot.
The outcomes for the sum of two dice can be described as a discrete uniform distribution?
No, it resembles a normal distribution, but discrete. sum --- Probability 2-----------1/36 3-----------2/36 4-----------3/36 5-----------4/26 6-----------5/36 7-----------6/36 8-----------5/36 9-----------4/36 10----------3/36 11----------2/36 12----------1/36
What is needed to develop a bionomial probability distribution?
A number of independent trials such that there are only two outcomes and the probability of "success" remains constant.
What are the conditions under which you can expect to be able to use a binomial distribution to model a probability distribution?
Two independent outcomes with constant probabilities.
What are four requirements for binomial distribution?
A binomial experiment is a probability experiment that satisfies the following four requirements:1. Each trial can have only two outcomes or outcomes that can be reduced to two outcomes. These outcomes can be considered as either success or failure.2. There must be a fixed number of trials.3. The outcomes of each trial must be independent of each other.4. The probability of a success must remain the same for each trial.
