Question

In: Math

Suppose that a certain random variable, X, has the following cumulative distribution function (cdf): F(x) =...

Suppose that a certain random variable, X, has the following cumulative distribution function (cdf):

F(x) = 0 x < 2

  0.25x2 – x + 1 2 ≤ x ≤ 4

1 4 < x

Find P(X > 2.5) (Round your answer to 4 decimal places)

  

Solutions

Expert Solution

answer:

given data from the question is,

the certain data randomly variable x is,

F(x) 0 x < 2

  0.25x2 – x + 1 2 ≤ x ≤ 4

1 4 < x

to find the probability ( X > 2.5) is ,.....

the given data cdf based to the this are write as the,

P(X<x) 0.25x2-x+1

now the probability is as the writes,

P(X>2.5)

now this are as the probability is the

1-P(X<2.5)

  1-(0.252.52-2.5+1) ( here the value of the (0.252.52-2.5+1) is the 0.0625

0.9375

0.9375

so finally the probability of the ( x 2.5 ) is the 0.9375

0.9375

Related Solutions

Let the continuous random variable X have probability density function f(x) and cumulative distribution function F(x)....
Let the continuous random variable X have probability density function f(x) and cumulative distribution function F(x). Explain the following issues using diagram (Graphs) a) Relationship between f(x) and F(x) for a continuous variable, b) explaining how a uniform random variable can be used to simulate X via the cumulative distribution function of X, or c) explaining the effect of transformation on a discrete and/or continuous random variable
Show that the cumulative distribution function for a random variable X with a geometric distribution is...
Show that the cumulative distribution function for a random variable X with a geometric distribution is F(x) = 0 for x < 0, F(x) = p for 0 <= x < 1, and, in general, F(x)= 1 - (1-p)^n for n-1 <= x < n for n = 2,3,....
Plot the probability mass function (PMF) and the cumulative distribution function (CDF) of 3 random variables...
Plot the probability mass function (PMF) and the cumulative distribution function (CDF) of 3 random variables following (1) binomial distribution [p,n], (2) a geometric distribution [p], and (3) Poisson distribution [?]. You have to consider two sets of parameters per distribution which can be chosen arbitrarily. The following steps can be followed: Setp1: Establish two sets of parameters of the distribution: For Geometric and Poisson distributions take two values of p (p1 and p2) and take two values of [?],...
Plot the probability mass function (PMF) and the cumulative distribution function (CDF) of 3 random variables...
Plot the probability mass function (PMF) and the cumulative distribution function (CDF) of 3 random variables following (1) binomial distribution [p,n], (2) a geometric distribution [p], and (3) Poisson distribution [?]. You have to consider two sets of parameters per distribution which can be chosen arbitrarily. The following steps can be followed
Plot the probability mass function (PMF) and the cumulative distribution function (CDF) of 3 random variables...
Plot the probability mass function (PMF) and the cumulative distribution function (CDF) of 3 random variables following (1) binomial distribution [p,n], (2) a geometric distribution [p], and (3) Poisson distribution [?]. You have to consider two sets of parameters per distribution which can be chosen arbitrarily. The following steps can be followed: Setp1: Establish two sets of parameters of the distribution: For Geometric and Poisson distributions take two values of p (p1 and p2) and take two values of [?],...
: Let X denote the result of a random experiment with the following cumulative distribution function...
: Let X denote the result of a random experiment with the following cumulative distribution function (cdf): 0, x <1.5 | 1/ 6 , 1.5<=x < 2 | 1/ 2, 2 <= x <5 | 1 ,x >= 5 Calculate ?(1 ? ≤ 6) and ?(2 ≤ ? < 4.5) b. Find the probability mass function (pmf) of ? d. If it is known that the result of the experiment is integer, what is the probability that the result is...
Considering X a continuous random variable defined by the distribution function f(x) = 0 if x<1...
Considering X a continuous random variable defined by the distribution function f(x) = 0 if x<1 -k +k/x if 1<= x < 2 1 if 2<x Find k.
If X is a random variable with CDF F(x) = e-e(µ-x)/β, where β > 0 and...
If X is a random variable with CDF F(x) = e-e(µ-x)/β, where β > 0 and -∞ < µ, x < ∞; calculate the median of X. Also, obtain the PDF of X.
Assume that a continuous random variable has a following probability density function: f ( x )...
Assume that a continuous random variable has a following probability density function: f ( x ) = { 1 10 x 4 2 ≤ x ≤ 2.414 0 o t h e r w i s e Use this information and answer questions 3a to 3g. Question a: Which of the following is a valid cumulative density function for the defined region ( 2 ≤ x ≤ 2.414)?    A.F x ( x ) = 1 50 x 5 −...
using excel   Plot the probability mass function (PMF) and the cumulative distribution function (CDF) of 3...
using excel   Plot the probability mass function (PMF) and the cumulative distribution function (CDF) of 3 random variables following (1) binomial distribution [p,n], (2) a geometric distribution [p], and (3) Poisson distribution [?]. You have to consider two sets of parameters per distribution which can be chosen arbitrarily. The following steps can be followed: Setp1: Establish two sets of parameters of the distribution: For Geometric and Poisson distributions take two values of p (p1 and p2) and take two values...
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT