The mean of a binomial probability distribution can be determined by multiplying the sample size times the probability of success.
It is 0.6
The probability is 0.4448, approx.
the variance is infinitely large and in the extreme case the probability distribution curve will simply be a horizontal line
Poisson and Binomial both the distribution are used for defining discrete events.You can tell that Poisson distribution is a subset of Binomial distribution. Binomial is the most preliminary distribution to encounter probability and statistical problems. On the other hand when any event occurs with a fixed time interval and having a fixed average rate then it is Poisson distribution.
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.
what is meant by a negative binomial distribution what is meant by a negative binomial distribution
Normal distribution is the continuous probability distribution defined by the probability density function. While the binomial distribution is discrete.
The mean of a binomial probability distribution can be determined by multiplying the sample size times the probability of success.
yes
It is 0.6
The binomial probability distribution is discrete.
Consider a binomial distribution with 10 trials What is the expected value of this distribution if the probability of success on a single trial is 0.5?
Nothing since it is impossible. No event can have 5 as the probability of success.
If you assume a binomial distribution, the variance is n*p*(1-p) where n is the number of voters = 30 p is the probability of support = 0.36 So variance = 30*0.36*0.64 = 6.912
In a symmetric binomial distribution, the probabilities of success and failure are equal, resulting in a symmetric shape of the distribution. In a skewed binomial distribution, the probabilities of success and failure are not equal, leading to an asymmetric shape where the distribution is stretched towards one side.
The probability is 0.4448, approx.