Probability
An unbiased coin is tossed $$5$$ times. Suppose that a variable $$X$$ is assigned the value $$k$$ when $$k$$ consecutive heads are obtained for $$k=3,4,5,$$ otherwise $$X$$ takes the value $$-1$$. The the expected value of $$X$$, is :
In a binomial distribution $$\mathrm{B} ($$n,p $$=\displaystyle \dfrac{1}{4})$$, if the probability of at least one success is greater than or equal to $$\displaystyle \dfrac{9}{10}$$ , then $$\mathrm{n}$$ is greater than
Given p= 1 4 ,q=1−p= 3 4 P(x≥1)≥ 9 10 ⇒1−P(x=0)≥ 9 10 P(x=0)=nC0p0qn=( 3 4 )n ⇒ 1 10 ≥( 3 4 )n ⇒( 3 4 )n≤ 1 10 ⇒n[log103−log104]≤−1 ⇒n≥ 1 log104−log103
An unbiased coin is tossed $$5$$ times. Suppose that a variable $$X$$ is assigned the value $$k$$ when $$k$$ consecutive heads are obtained for $$k=3,4,5,$$ otherwise $$X$$ takes the value $$-1$$. The the expected value of $$X$$, is :
In a workshop, there are five machines and the probability of any one of them to be out of service on day is $$\dfrac{1}{4}$$. If the probability that at most two machines will be out of service on the same day is $$\left(\dfrac{3}{4} \right)^3 k$$, then k is equal to :
If the mean and the variance of a binomial variate X are 2 and 1 respectively, then probability that X takes a value greater than or equal to one is
The minimum number of times one has to toss fair coins so that probability of observing at least one head is at least $$90$$% is:
An unbiased coin is tossed eight times. The probability of obtaining at least one head and at least one tail is.
An experiment succeeds twice as often as it fails. The probability of at least $$1$$ successes in the six trials of this experiment is:
A multiple choice examination has $$5$$ questions. Each question has three alternative answers of which exactly one is correct. The probability that a student will get $$4$$ or more correct answers just by guessing is
Consider 5 independent Bernoulli trials each with probability of success $$\mathrm{p}$$. If the probability of at least one failure is greater than or equal to $$\displaystyle \frac{31}{32}$$, then $$\mathrm{p}$$ lies in the interval.
If in a binomial distribution $$n=4,P(X=0)=\cfrac { 16 }{ 81 } $$, then $$P(X=4)$$ equals
The odds in favour of India winning any cricket match is $$2 : 3$$. What is the probability that if India plays $$5$$ matches, it wins exactly $$3$$ of them?