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It is the so-called "half-normal distribution."
Specifically, let X be a standard normal variate with cumulative distribution function F(z). Then its cumulative distribution function G(z) is given by
Prob(|X| < z)
= Prob(-z < X < z)
= Prob(X < z) - Prob(X < -z)
= F(z) - F(-z).
Its probability distribution function g(z), z >= 0, therefore equals
g(z) = Derivative of (F(z) - F(-z))
= f(z) + f(-z) {by the Chain Rule}
= 2f(z)
because of the symmetry of f with respect to zero. In other words, the probability distribution function is zero for negative values (they cannot be absolute values of anything) and otherwise is exactly twice the distribution of the standard normal.
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Is the normal probability distribution applied to a continuous random variable?
Yes.
What is the z value for a normal distribution?
If a random variable X has a Normal distribution with mean m and standard deviation s, then z = (X - m)/s has a Standard Normal distribution. That is, Z has a Normal distribution with mean 0 and standard deviation 1. Probabilities for a general Normal distribution are extremely difficult to obtain but values for the Standard Normal have been calculated numerically and are widely tabulated. The z-transformation is, therefore, used to evaluate probabilities for Normally distributed random variables.
The mean or expected value of the distribution of a discrete random variable is?
30.47
What is commulative frequency distribution?
The cumulative frequency distribution for a value x of a random variable X, is a count of the number of observations in which X is less than or equal to x. The cumulative frequency distribution for a value x of a random variable X, is a count of the number of observations in which X is less than or equal to x. The cumulative frequency distribution for a value x of a random variable X, is a count of the number of observations in which X is less than or equal to x. The cumulative frequency distribution for a value x of a random variable X, is a count of the number of observations in which X is less than or equal to x.
If the outcomes of a random variable follow a Poisson distribution then their?
means equal the standard deviation
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.
Is the normal probability distribution applied to a continuous random variable?
Yes.
What does the mean have to do with a normal distribution?
Almost all statistical distribution have a mean. It is the expected value of the random variable which is distributed according to that function.
Can the Poisson distribution be a continuous random variable or a discrete random variable?
True
What is the Test for normal distribution?
Normal Distribution is a key to Statistics. It is a limiting case of Binomial and Poisson distribution also. Central limit theorem converts random variable to normal random variable. Also central limit theorem tells us whether data items from a sample space lies in an interval at 1%, 5%, 10% siginificane level.
Can the variance of a normally distributed random variable be negative?
No. The variance of any distribution is the sum of the squares of the deviation from the mean. Since the square of the deviation is essentially the square of the absolute value of the deviation, that means the variance is always positive, be the distribution normal, poisson, or other.
Can the time to microwave a bag of popcorn using the automatic setting be treated as a random variable having a normal distribution?
no
What you mean by saying random variable is approximately normally distributed?
Exactly "what it says on the tin"! The distribution is nearly, but not quite, the standard normal, or Gaussiam distribution.
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.
How to find z scores?
If a random variable X has a Normal distribution with mean M and variance S2, then Z = (X - M)/S
What is the z value for a normal distribution?
If a random variable X has a Normal distribution with mean m and standard deviation s, then z = (X - m)/s has a Standard Normal distribution. That is, Z has a Normal distribution with mean 0 and standard deviation 1. Probabilities for a general Normal distribution are extremely difficult to obtain but values for the Standard Normal have been calculated numerically and are widely tabulated. The z-transformation is, therefore, used to evaluate probabilities for Normally distributed random variables.
What will be the sampling distribution of the mean for a sample size of one?
It will be the same as the distribution of the random variable itself.
