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What is the binomial probability if the mean value is 3 and the variance is 1.2?
Wiki User
∙ 9y ago
It is 0.6
Wiki User
∙ 9y ago
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Why not simply use the mean value of the regressand as its best value?
Variance" is a mesaure of the dispersion of the probability distribution of a random variable. Consider two random variables with the same mean (same aver-age value). If one of them has a distribution with greater variance, then, roughly speaking, the probability that the variable will take on a value far from the mean is greater.
The mean of a binomial probability distribution can be determined by multiplying?
The mean of a binomial probability distribution can be determined by multiplying the sample size times the probability of success.
In a normal distribution with mean 80 and variance 144 squared what is the probability above 100?
The probability is 0.4448, approx.
What requirements are necessary for a normal probability distibution to be a standard normal probability distribution?
The mean must be 0 and the variance must be 1.
When referring to the normal probability there is not just one there is a family of distributions?
A family that is defined by two parameters: the mean and variance (or standard deviation).
Can you please tell me the variance and the standard deviation for n equals 80 and p equals 0.3?
For a binomial probability distribution, the variance is n*p*q which is 80*.3*.7 = 16.8. The standard deviation is square root of the variance which is 4.099; rounded is 4.1. The mean for a binomial probability distribution is n*p or 80*.3 or 24.
The mean of a binomial probability distribution can be determined by multiplying?
The mean of a binomial probability distribution can be determined by multiplying the sample size times the probability of success.
Why not simply use the mean value of the regressand as its best value?
Variance" is a mesaure of the dispersion of the probability distribution of a random variable. Consider two random variables with the same mean (same aver-age value). If one of them has a distribution with greater variance, then, roughly speaking, the probability that the variable will take on a value far from the mean is greater.
What are mean and variance of negative binomial distribution by conclusion?
what is meant by a negative binomial distribution what is meant by a negative binomial distribution
Is in binomial distribution mean always greater then variance?
yes
Distinguish between mean deviation and standard deviation?
The mean deviation for any distribution is always 0 and so conveys no information whatsoever. The standard deviation is the square root of the variance. The variance of a set of values is the sum of the probability of each value multiplied by the square of its difference from the mean for the set. A simpler way to calculate the variance is Expected value of squares - Square of Expected value.
In a normal distribution with mean 80 and variance 144 squared what is the probability above 100?
The probability is 0.4448, approx.
What requirements are necessary for a normal probability distibution to be a standard normal probability distribution?
The mean must be 0 and the variance must be 1.
What is the binomial theorem formula for probability?
I expect you mean the probability mass function (pmf). Please see the right sidebar in the linked page.
Why binomial distribution can be approximated by Poisson distribution?
Only in certain circumstances:The probability of success, p, in each trial must be close to 0.Then, for the random variable, X = number of successes in n trials, the mean is npand the variance is np(1-p). But since p is close to 0, (1-p) is close to 1 and so np(1-p) is close to np.That is, the mean of the distribution is close to its variance. This is a characteristic of the Poisson distribution.Furthermore, the other characteristics of the distribution: constant probability, independence are met so the Binomial can be approximated by the Poisson.It is possible to prove this analytically but the limitations of this browser - especially in terms of mathematical notation - preclude that.Only in certain circumstances:The probability of success, p, in each trial must be close to 0.Then, for the random variable, X = number of successes in n trials, the mean is npand the variance is np(1-p). But since p is close to 0, (1-p) is close to 1 and so np(1-p) is close to np.That is, the mean of the distribution is close to its variance. This is a characteristic of the Poisson distribution.Furthermore, the other characteristics of the distribution: constant probability, independence are met so the Binomial can be approximated by the Poisson.It is possible to prove this analytically but the limitations of this browser - especially in terms of mathematical notation - preclude that.Only in certain circumstances:The probability of success, p, in each trial must be close to 0.Then, for the random variable, X = number of successes in n trials, the mean is npand the variance is np(1-p). But since p is close to 0, (1-p) is close to 1 and so np(1-p) is close to np.That is, the mean of the distribution is close to its variance. This is a characteristic of the Poisson distribution.Furthermore, the other characteristics of the distribution: constant probability, independence are met so the Binomial can be approximated by the Poisson.It is possible to prove this analytically but the limitations of this browser - especially in terms of mathematical notation - preclude that.Only in certain circumstances:The probability of success, p, in each trial must be close to 0.Then, for the random variable, X = number of successes in n trials, the mean is npand the variance is np(1-p). But since p is close to 0, (1-p) is close to 1 and so np(1-p) is close to np.That is, the mean of the distribution is close to its variance. This is a characteristic of the Poisson distribution.Furthermore, the other characteristics of the distribution: constant probability, independence are met so the Binomial can be approximated by the Poisson.It is possible to prove this analytically but the limitations of this browser - especially in terms of mathematical notation - preclude that.
How is standard deviation found?
Formally, the standard deviation is the square root of the variance. The variance is the mean of the squares of the difference between each observation and their mean value. An easier to remember form for variance is: the mean of the squares minus the square of the mean.
What is the different between standard normal distribution and normal distribution?
A normal distribution can have any value for its mean and any positive value for its variance. A standard normal distribution has mean 0 and variance 1.
