Let x be a continuous random variable with a uniform
distribution. x can take on values between x=20 and x=54. Compute
the probability, P(26<x<39).
P(26<x<39)= ? (Give at least 3 decimal
places)
Let x be a continuous random variable with a uniform
distribution. x can take on values between x=13 and x=52. Compute
the probability, P(27<x<36).
P(27<x<36)= ? (Give at least 3 decimal places)
Solution :
Given that,
a = 20
b = 54
P(c < x < d) = (d - c) / (b - a)
P(26 < x < 39) = (39 - 26) / (54 - 20) = 13 / 34 = 0.3823
Solution :
Given that,
a = 13
b = 52
P(27 < x < 36) = (36 - 27) / (52 - 13) = 9 / 39 = 0.2308
Let x be a continuous random variable with a uniform distribution. x can take on values...
Let the random variable X have a continuous uniform distribution with a minimum value of 115 and a maximum value of 165. What is P(x > 120.20 X < 159.28) ? Round your response to at least 3 decimal places. Number Which of the following statements are TRUE? There may be more than one correct answer, select all that are true. In a normal distribution, the mean and median are equal. If Z is a standard normal random variable, then...
Let the random variable X have a continuous uniform distribution with a minimum value of 110 and a maximum value of 165. What is P(X< 98.697 U X > 141.85)? Round your response to at least 3 decimal places. Number
Let the random variable X have a continuous uniform distribution with a minimum value of 120 and a maximum value of 170. What isP(X>141.96|X<148.23)? Round your response to at least 3 decimal places.
Let X be a random variable following a continuous uniform distribution from 0 to 10. Find the conditional probability P(X >3 X < 5.5). Chebyshev's theorem states that the probability that a random variable X has a value at most 3 standard deviations away from the mean is at least 8/9. Given that the probability distribution of X is normally distributed with mean ji and variance o”, find the exact value of P(u – 30 < X < u +30).
Question 3: Let X be a continuous random variable with cumulative distribution function FX (x) = P (X ≤ x). Let Y = FX (x). Find the probability density function and the cumulative distribution function of Y . Question 3: Let X be a continuous random variable with cumulative distribution function FX(x) = P(X-x). Let Y = FX (x). Find the probability density function and the cumulative distribution function of Y
Let X be a random variable that has a binomial distribution with n = 15 and probability of success p=0.87. What is P(X > 12)? Give your response to at least 3 decimal places. Number
A random variable follows the continuous uniform distribution between 20 and 50 a) Calculate the probabilities below for the distribution. 1) P(x≤40) 2) P(x=39) b) What are the mean and standard deviation of this distribution?
Consider the continuous random variable X, which has a uniform distribution over the interval from 0.46 to 0.96, what is the probability that X will take on a value between 0.62 and 0.84?
5. A continuous random variable X follows a uniform distribution over the interval [0, 8]. (a) Find P(X> 3). (b) Instead of following a uniform distribution, suppose that X assumes values in the interval [0, 8) according to the probability density function pictured to the right. What is h the value of h? Find P(x > 3). HINT: The area of a triangle is base x height. 2 0 0
please 6 and 7 6. (3.18, 20) A continuous random variable X that can assume values between r = 2 and x = 5 has a density function given by f(x) = 2(1+x)/27. Find the Cumulative Distribution Function F(x). 7. (3.14) The waiting time, in hours, between successive speeders spotted by a radar unit is a continuous random variable with a cumulative distribution function x<0, F(x) = -e-41, x20 Find the probability of waiting between 3 to 7 minutes a)...