Let x ~ U (0,1) be a random variable and find the density function of y = - INX RT

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• 1. Let x ~ U (- 1,1) be the random variable, and find the density function of y = e ^ X
• 2. Let the distribution function of continuous random variable X be f (x), and the density function be f (x), then why is p (x = x) = 0?
• 3. Let the distribution function of random variable X be f (x) = a + the distribution function of known random variable X be f (x) = a + B arctanx, find the values of a and B, and find P (- 1) （1）∵F(-∞)=0，F(+∞)=1 im(x→-∞)F(x)=A-Bπ/2=0; LIM (x → + ∞) f (x) = a + B π / 2 = 1; why use a minus sign and a plus sign here? How does π / 2 come from How can A-B π / 2 = 0 be solved? Bπ/2=1/2？ Why?
• 4. Let the probability density of random variable X be f (x) = {x, 0 ≤ x ＜ 1; 2-x, 1 ≤ x ＜ 2; 0, others} to find the distribution function f (x) of X,
• 5. The density function of random variable x is f (x) = 1 / 2E ^ - | x |, X belongs to R, find the distribution function of X
• 6. Let the joint density function of two-dimensional random variable (x, y) be f (x, y) = {1 / Π r square, x square + y square ≤ r square {0} Explain whether X and y are related, whether X and y are independent, and why
• 7. Let the density function of random variable X be f (x) = the - K ^ 2x ^ 2 power of CXE, x > = 0, 0, X
• 8. It is known that the density function of continuous random variable x is f (x) = x, 0 Let's go over the subject again It is known that the density function of continuous random variable x is F (x) = x when 0
• 9. Two dimensional random variables (x, y) in the region D = {(x, y) | 0
• 10. Suppose that the random variable x obeys the uniform distribution on the interval of (0,1), then the density function of the random variable y = x & #
• 11. Let the random variable x ~ U (0,1), try to find: (1) the distribution function and density function of y = e ^ X; (2) the distribution function and density function of Z = - 2x
• 12. Probability density function and distribution function of random variables Let the probability density function of two-dimensional random variables (x, y) be xe^(-y),0
• 13. Probability theory and distribution function of mathematical statistics The absolute value of random variable x is not greater than 1, P {x = - 1} = 1 / 8, P {x = 1} = 1 / 4; in the event {- 1} In order to attract the audience, specially register a new number to send points~
• 14. Probability theory and distribution function of random variables in mathematical statistics Let the distribution law of random variable X be X -1 2 3 p 0.25 0.5 0.25 Finding P {2 ≤ x ≤ 3} through the distribution function of X The solution is p {2 ≤ x ≤ 3} = f (3) - f (2) + P {x = 2} I want to ask why we add "P {x = 2}" and what is the relationship between the equal sign of 2 ≤ x ≤ 3
• 15. Probability theory and distribution function of mathematical statistics random variable First of all, the definition is as follows: FX (x) = P ({w belongs to R: X (W))
• 16. In probability theory, if the probability density f (x) of continuous random variable changes the value of finite points of F (x), f (x) is still the probability density. Why?
• 17. Probability theory: let the probability density of random variable X be f (x) = {A / X & # 178;, x > 10; 0, X
• 18. If the random variables X and y are independent of each other and obey the uniform distribution on the interval (0,1), then the following random variables obey the uniform distribution A.x & # 178; b.x + y, C. (x, y) d.x-y, please give me a process,
• 19. Let the random variables X and y be independent and obey the uniform distribution on the interval [0, a], and then calculate the probability density of the random variable z = x / y
• 20. Suppose that the random variable x obeys the uniform distribution on the interval [- 1,1], then the probability density of y = 2-x is obtained