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An important discrete probability distribution is
- a)Poisson distribution.
- b)Normal distribution.
- c)Cauchy distribution.
- d)Log normal distribution.
Correct answer is option 'A'. Can you explain this answer?
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An important discrete probability distribution isa)Poisson distributio...
Explanation:
Discrete Probability Distribution: A discrete probability distribution is a probability distribution characterized by a probability mass function (PMF) that maps each possible value of a discrete random variable to a probability. The PMF describes the probability that a random variable takes on a certain value.
Poisson Distribution: Poisson distribution is a discrete probability distribution that expresses the probability of a given number of events occurring in a fixed interval of time or space, assuming that these events occur with a known constant rate and independently of the time since the last event. It is used to model the number of occurrences of an event within a specific time or space interval.
Normal Distribution: Normal distribution is a continuous probability distribution that describes the distribution of a random variable that is normally distributed. It is commonly used to model the distribution of many natural phenomena, such as height, weight, and IQ.
Cauchy Distribution: Cauchy distribution is a continuous probability distribution that has no mean or variance. It is used to model extreme events that are rare but have a high impact.
Log Normal Distribution: Log normal distribution is a continuous probability distribution that is used to model variables that are the product of many small independent factors.
Conclusion: Among the given options, the Poisson distribution is an important discrete probability distribution, as it is commonly used to model the number of occurrences of an event within a specific time or space interval.
Discrete Probability Distribution: A discrete probability distribution is a probability distribution characterized by a probability mass function (PMF) that maps each possible value of a discrete random variable to a probability. The PMF describes the probability that a random variable takes on a certain value.
Poisson Distribution: Poisson distribution is a discrete probability distribution that expresses the probability of a given number of events occurring in a fixed interval of time or space, assuming that these events occur with a known constant rate and independently of the time since the last event. It is used to model the number of occurrences of an event within a specific time or space interval.
Normal Distribution: Normal distribution is a continuous probability distribution that describes the distribution of a random variable that is normally distributed. It is commonly used to model the distribution of many natural phenomena, such as height, weight, and IQ.
Cauchy Distribution: Cauchy distribution is a continuous probability distribution that has no mean or variance. It is used to model extreme events that are rare but have a high impact.
Log Normal Distribution: Log normal distribution is a continuous probability distribution that is used to model variables that are the product of many small independent factors.
Conclusion: Among the given options, the Poisson distribution is an important discrete probability distribution, as it is commonly used to model the number of occurrences of an event within a specific time or space interval.
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An important discrete probability distribution isa)Poisson distributio...
Binomial and Poisson are discrete probability distributions whereas others are continuous probability distribution
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An important discrete probability distribution isa)Poisson distribution.b)Normal distribution.c)Cauchy distribution.d)Log normal distribution.Correct answer is option 'A'. Can you explain this answer?
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