How do you know when to use a specific distribution? For example, when would we use the Normal, binomial, grometric, hypergeometric, or negative binomial distribution? When doing so, when do we know if is is a discrete or continuous distribution?

snowlovelydayM
2021-09-16
Answered

How do you know when to use a specific distribution? For example, when would we use the Normal, binomial, grometric, hypergeometric, or negative binomial distribution? When doing so, when do we know if is is a discrete or continuous distribution?

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Szeteib

Answered 2021-09-17
Author has **102** answers

Step 1

To use a specific distribution one should know the properties of that distribution. For example if the data distribution is symmetric and have bell shape curve then we use a normal distribution. If the data distribution have two outcomes one success and one failure out of n trials then we use binomial distribution etc.

Step 2

The probability distributions are classified as discrete and continuous probability distributions based on the random variable.

If the variable can take any value between two particular values then we say it as continuous distribution. If the variable cannot take any value between particular values then we say it is discrete probability distribution.

For example in binomial probability distribution where n is total trials and p is probability of success and x is number of success. Here x can take only values 0,1,2,3,4.....n. x cannot take values between 1 and 2. So we can say that the binomial distribution is discrete probability distribution.

For example if we find a distribution with data of weights of students in a school between 60lbs and 120 lbs then the weights can take any value between them. In this case we call the distribution to be continuous probability distribution.

Normal DIstribution, Exponential Distribution, - Continuous Distribution

Binomial Distribution, geometric Distribution, Hypergeometric Distribution, Negative binomial Distribution Poisson Distribution - Discrete Distribution

To use a specific distribution one should know the properties of that distribution. For example if the data distribution is symmetric and have bell shape curve then we use a normal distribution. If the data distribution have two outcomes one success and one failure out of n trials then we use binomial distribution etc.

Step 2

The probability distributions are classified as discrete and continuous probability distributions based on the random variable.

If the variable can take any value between two particular values then we say it as continuous distribution. If the variable cannot take any value between particular values then we say it is discrete probability distribution.

For example in binomial probability distribution where n is total trials and p is probability of success and x is number of success. Here x can take only values 0,1,2,3,4.....n. x cannot take values between 1 and 2. So we can say that the binomial distribution is discrete probability distribution.

For example if we find a distribution with data of weights of students in a school between 60lbs and 120 lbs then the weights can take any value between them. In this case we call the distribution to be continuous probability distribution.

Normal DIstribution, Exponential Distribution, - Continuous Distribution

Binomial Distribution, geometric Distribution, Hypergeometric Distribution, Negative binomial Distribution Poisson Distribution - Discrete Distribution

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