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How does a discrete probability distribution differ from a continuous probability distribution?

Anonymous

∙ 15y ago

Updated: 4/28/2022

A discrete probability distribution is defined over a set value (such as a value of 1 or 2 or 3, etc). A continuous probability distribution is defined over an infinite number of points (such as all values between 1 and 3, inclusive).

Wiki User

∙ 15y ago

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Q: How does a discrete probability distribution differ from a continuous probability distribution?

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How does probability differ from actuality?

Probability is the chance of some outcome while actuality is the realistic chance and actual outcome of an event.

How does the shape of the normal distribution differ from the shapes of the uniform and exponential distributions?

the normal distribution is a bell shape and expeonential is rectangular

How does the experimental result differ from the theoretical in terms of accuracy?

Provided that the correct model is used, the theoretical probability is correct. The experimental probability tends towards the theoretical value as the number of trials increases.Provided that the correct model is used, the theoretical probability is correct. The experimental probability tends towards the theoretical value as the number of trials increases.Provided that the correct model is used, the theoretical probability is correct. The experimental probability tends towards the theoretical value as the number of trials increases.Provided that the correct model is used, the theoretical probability is correct. The experimental probability tends towards the theoretical value as the number of trials increases.

IF two variables that have the same mean and standard deviation have the same distribution?

No, a distribution can have infinitely many moments: the first is the mean, the second variance. Then there are skewness (3), kurtosis (4), hyperskewness (5), hyperflatness (6) and so on.If mk represents the kth moment, thenmk = E[(X - m1)k] where E is the expected value.It is, therefore, perfectly possible for m1 and m2 to be the same but for the distribution to differ at the higher moments.

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it differs becaus eit shows differ amount of data and it gives a differ piont of point of numbers

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