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It is a variable that can take a number of different values. The probability that it takes a value in any given range is determined by a random process and the value of that probability is given by the probability distribution function.

It is a variable that can take a number of different values. The probability that it takes a value in any given range is determined by a random process and the value of that probability is given by the probability distribution function.

It is a variable that can take a number of different values. The probability that it takes a value in any given range is determined by a random process and the value of that probability is given by the probability distribution function.

It is a variable that can take a number of different values. The probability that it takes a value in any given range is determined by a random process and the value of that probability is given by the probability distribution function.

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โˆ™ 2014-10-17 19:21:31
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โˆ™ 2014-10-17 19:21:31

It is a variable that can take a number of different values. The probability that it takes a value in any given range is determined by a random process and the value of that probability is given by the probability distribution function.

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Q: What is the meaning of random variable in probability distribution?
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What gives the probability of each random variable?

The marginal probability distribution function.


What is the likelihood of the probability 0 to infinity?

The answer depends on the probability distribution function for the random variable.


Is the normal probability distribution applied to a continuous random variable?

Yes.


How many random variables are needed to plot a probability distribution?

A probability density function can be plotted for a single random variable.


How do you get the median of a continuous random variable?

You integrate the probability distribution function to get the cumulative distribution function (cdf). Then find the value of the random variable for which cdf = 0.5.


What is the probability the random variable will assume a value between 40 and 60?

It depends on what the random variable is, what its domain is, what its probability distribution function is. The probability that a randomly selected random variable has a value between 40 and 60 is probably quite close to zero.


Define a normal random variable?

I have included two links. A normal random variable is a random variable whose associated probability distribution is the normal probability distribution. By definition, a random variable has to have an associated distribution. The normal distribution (probability density function) is defined by a mathematical formula with a mean and standard deviation as parameters. The normal distribution is ofter called a bell-shaped curve, because of its symmetrical shape. It is not the only symmetrical distribution. The two links should provide more information beyond this simple definition.


What are the 2 conditions that determine a probability distribution?

The value of the distribution for any value of the random variable must be in the range [0, 1]. The sum (or integral) of the probability distribution function over all possible values of the random variable must be 1.


Difference between a random variable and a probability distribution is?

A random variable is a variable that can take different values according to a process, at least part of which is random.For a discrete random variable (RV), a probability distribution is a function that assigns, to each value of the RV, the probability that the RV takes that value.The probability of a continuous RV taking any specificvalue is always 0 and the distribution is a density function such that the probability of the RV taking a value between x and y is the area under the distribution function between x and y.


A random variable and a probability distribution?

The number of 6s in 37 rolls of a loaded die and binomial.


What is the probability that a Poisson random variable x is equal to 5...?

It depends on the parameter - the mean of the distribution.


What is the difference between probability distribution and probability density function?

A probability density function assigns a probability value for each point in the domain of the random variable. The probability distribution assigns the same probability to subsets of that domain.

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