Thegiven PDF is
1) The condition for PDF is
![4 f(x)dx 1 1 4 k(-x25x- 4)dx 1 k-x3/35x2/2-4x] 1 1 2 2 k OINN/o](http://img.homeworklib.com/questions/58a5f440-7ba4-11eb-abc5-f5225433814f.png?x-oss-process=image/resize,w_560)
2) The expected value is

3) The mode
is such that

4) The CDF is
![Fx(x) f(t)dt 1 k(-t2 5t 4)dt Fx(x) = Fx(x) k(-t3/35t2/2 4t] x3 1 5(x2- 1) 4(x-1)) Fx(x) k 3 2 5x2 4Xt x3 2 11 ;1 x 4 6 Fx(x)](http://img.homeworklib.com/questions/75e4fa10-7ba4-11eb-9dd6-81c17967562b.png?x-oss-process=image/resize,w_560)
5) The probability,

6) The median is such that
.
From part (5), we see that
The shape of the distribution is an inverted parabola, symmetric
about the lin
.
Thegiven PDF is
1) The condition for PDF is
![4 f(x)dx 1 1 4 k(-x25x- 4)dx 1 k-x3/35x2/2-4x] 1 1 2 2 k OINN/o](http://img.homeworklib.com/questions/7d92d590-7ba4-11eb-a983-d9816e8c768d.png?x-oss-process=image/resize,w_560)
2) The expected value is

3) The mode
is such that

4) The CDF is
![Fx(x) f(t)dt 1 k(-t2 5t 4)dt Fx(x) = Fx(x) k(-t3/35t2/2 4t] x3 1 5(x2- 1) 4(x-1)) Fx(x) k 3 2 5x2 4Xt x3 2 11 ;1 x 4 6 Fx(x)](http://img.homeworklib.com/questions/90eebd30-7ba4-11eb-bce2-3de004da598e.png?x-oss-process=image/resize,w_560)
5) The probability,

6) The median is such that
.
From part (5), we see that
The shape of the distribution is an inverted parabola, symmetric
about the lin
.
The random variable X has probability density function k(x25x-4) 1<x<4 otherwise -{ f(x) 1. Show thatk....
The random variable X has probability density function f (x) = k(−x²+5x−4) 1 ≤ x ≤ 4 or =0 1 Show that k = 2/9 Find 2 E(X), 3 the mode of X, 4 the cumulative distribution function F(X) for all x. 5 Evaluate P(X ≤ 2.5). 6 Deduce the value of the median and comment on the shape of the distribution.
(1) Suppose that X is a continuous random variable with probability density function 0<x< 1 f() = (3-X)/4 i<< <3 10 otherwise (a) Compute the mean and variance of X. (b) Compute P(X <3/2). (c) Find the first quartile (25th percentile) for the distribution.
6. Let X be a continuous random variable whose probability density function is: 0, x <0, x20.5 Find the median un the mode. 7. Let X be a continuous random variable whose cumulative distribution function is: F(x) = 0.1x, ja 0S$s10, Find 1) the densitv function of random variable U-12-X. 0, ja x<0, I, ja x>10.
Suppose the random variable X has probability density function (pdf) - { -1 < x<1 otherwise C fx (x) C0 : where c is a constant. (a) Show that c = 1/7; (b) Graph fx (х); (c) Given that all of the moments exist, why are all the odd moments of X zero? (d) What is the median of the distribution of X? (e) Find E (X2) and hence var X; (f) Let X1, fx (x) What is the limiting...
2x 0<x<1 Let X be a continuous random variable with probability density function f(x)= To else The cumulative distribution function is F(x). Find EX.
4. (30pts) A continuous random variable X has the probability density function: hx - 1 sx 32 f(x) =Jo-hx 2 x 3 0 x >3 which ean bo graphed as f(x) 1 2 a) Find h which makes f(x) a valid probability density function b) Find the expected value E(X) of the probability density function f(x) c) Find the cumulative distribution function F(x). Show all you work
b. Let X be a continuous random variable with probability density function f(x) = kx2 if – 1 < x < 2 ) otherwise Find k, and then find P(|X| > 1/2).
Homework help with 7.63 please
7.63 Let the random variable X have probability density function f(x)= -π/2 < x <π/2. Find the probability density function of Y sin X by the (a) cumulative distribution function technique, (b) transformation technique. dx1 Hint: The derivative oh-arcsiny is
2.5.6. The probability density function of a random variable X is given by f(x) 0, otherwise. (a) Find c (b) Find the distribution function Fx) (c) Compute P(l <X<3)
1. 20 points Let X be a random variable with the following probability density function: f(x)--e+1" with ? > 0, ? > 0, constants x > ?, (a) 5 points Find the value of constant c that makes f(x) a valid probability mass function. (b) 5 points Find the cumulative distribution function (CDF) of X.