For a binomial distribution with mean 4 and standard deviation \(\sqrt{3}\), what is the value of \(P(X=0)\)?
\(\left(\dfrac{3}{4}\right)^{16}\)
For a binomial distribution, mean \(np=4\) and variance \(npq=3\), so \(q=\frac{npq}{np}=\frac{3}{4}\) and \(p=\frac{1}{4}\), giving \(n=\frac{np}{p}=16\). Then \(P(X=0)={}^{n}C_{0}\,p^{0}q^{n}=q^{n}=\left(\frac{3}{4}\right)^{16}\).
In a Binomial distribution, the mean is three times its variance. What is the probability of exactly 3 successes out of 5 trials?
If mean and variance of a Binomial variate X are 2 and 1 respectively, then the probability that X takes a value greater than 1 is
Let the random variables X follow B (6, p) If \(16{\rm{\;P\;}}\left( {{\rm{X}} = 4} \right) = {\rm{P\;}}\left( {{\rm{X}} = 2} \right)\) , then what is the value of p
Consider a random variable X which follows Binomial distribution with parameters n = 10 and \(\rm p = \dfrac{1}{5}\) . Then Y = 10 - X follows Binomial distribution with parameters n' and p' respectively given by
If a fair die is rolled 4 times, then what is the probability that there are exactly 2 sixes?
What is the probability that no one out of 6 workers suffers from a disease?
8 coins are tossed simultaneously. The probability of getting at least 6 heads is
A medicine is known to be 75% effective to cure a patient. If the medicine is given to 5 patients, what is the probability that at least one patient is cured by this medicine?
The mean and standard deviation of a binomial distribution are 12 and 2 respectively. What is the number of trails?
Seven unbiased coins are tossed 128 times. In how many throws would you find at least three heads?
In a Binomial distribution, the mean is three times its variance. What is the probability of exactly 3 successes out of 5 trials?
If mean and variance of a Binomial variate X are 2 and 1 respectively, then the probability that X takes a value greater than 1 is
For Binomial distribution, n = 10 and p = 0.6, E(X 2) (second moment about origin) is:
Find out the fallacy if any in the statement:
“The mean and the variance of a binomial distribution is 16.2 and 29.4 respectively.”
If log e(x) is normally distributed with mean 1 and variance 4, then P(0.5 < x < 2) is:
(where the area between z = 0 and z = 0.25 is 0.0987 and the area between z = 0 and z = 0.5 is 0.1915)