y1 | |||
y2 | 2 | 4 | Total |
0 | 1/8 | 3/8 | 1/2 |
1 | 1/4 | 1/8 | 3/8 |
3 | 0 | 1/8 | 1/8 |
Total | 3/8 | 5/8 | 1 |
marginal distribution of Y1:
y1 | P(y1) | y1P(y1) | y1^2P(y1) |
2 | 3/8 | 0.7500 | 1.5000 |
4 | 5/8 | 2.5000 | 10.0000 |
total | 1.0000 | 3.2500 | 11.5000 |
E(y1) | = | 3.2500 | |
E(y1^2) | = | 11.5000 | |
Var(y1)=σy= | E(y1^2)-(E(y1))^2 | 0.9375 |
marginal distribution of Y2:
y2 | P(y2) | y2P(y2) | y2^2P(y2) |
0 | 1/2 | 0.0000 | 0.0000 |
1 | 3/8 | 0.3750 | 0.3750 |
3 | 1/8 | 0.3750 | 1.1250 |
total | 1 | 0.75 | 1.5 |
E(y2) | = | 0.7500 | |
E(y2^2) | = | 1.5000 | |
Var(y2)= | E(y2^2)-(E(y2))^2 | 0.9375 |
E(y1*Y2) =0*2*1/8+0*4*3/8+1*2*2/8+1*4*1/8+3*2*0+3*4*1/8=2.500
a)
Covar(y1,y2)=E(y1y2)-E(Y1)*E(y2)= | 1/16 = | 0.0625 |
b)
Correlation coefficient =Cov(y1,y2)/√(σy1*σy2)= | 1/15 = | 0.0667 |
yi 24 The joint probability function of Y1 and Y2 is given. 0 1/8 3/8 Y2...
yi 24 . The joint probability function of Y1 and Y2 is given. 0 1/8 3/8 y2 1 2/8 1/8 3 0 1/8 Find (a) F(3, 2), (b) E(Y1), (c) p2(0) and (d) p(y2 = 1|y1 = 4). Ans (a) 3/8 (b) 13/4 (c) 1/2 (d) 1/5
Let Y1 have the joint probability density function given by and Y2 k(1 y2), 0 s y1 y2 1, lo, = elsewhere. (a) Find the value of k that makes this a probability density function k = (b) Find P 1 (Round your answer to four decimal places.)
2. Let the random variables Y1 and Y, have joint density Ayſy22 - y2) 0<yi <1, 0 < y2 < 2 f(y1, y2) = { otherwise Stom.vn) = { isiml2 –») 05451,05 ms one a independent, amits your respon a) Are Y1 and Y2 independent? Justify your response. b) Find P(Y1Y2 < 0.5). on the
Let Y1, Y2 have the joint density f(y1,y2) = 4y1y2 for 0 ≤ y1,y2 ≤ 1 = 0 otherwise (a) (8 pts) Calculate Cov(Y1, Y2). (b) (3 pts) Are Y1 and Y2 are independent? Prove your answer rigorously. (c) (6 pts) Find the conditional mean E(Y2|Y1 = 1). 3
Let Yı, Y, have the joint density S 2, 0 < y2 <yi <1 f(y1, y2) = 0, elsewhere. Use the method of transformation to derive the joint density function for U1 = Y/Y2,U2 = Y2, and then derive the marginal density of U1.
2. Suppose the variables Y1 and Y2 have the following properties: 2. Suppose the variables Yi and Y2 have the following properties: E(%) = 4, Var(%) = 19,E(%) = 6.5, Var(%) = 5.25,E(,%) = 30 Calculate the following; please show the underlying work: a) (3 pts) Cov(Y,Y2) b) (3 pts) Cov(4Y1,3Y2) c) (3 pts) Cov(4h, 5-½) d) (6 pts) Find the correlation coefficient between 1 + 3, and 3-2%
(pts) 1. The joint probability density of X and Y is given by . 0<x<1 and 0 <y<2 otherwise d) Find Cov(X,Y). a) Verify that this is a joint probability density function. b) Find P(x >Y). ) Find Pſy>*<51 c) Find the correlation coefficient of X and Y (Pxy).
(8pts) 1. The joint probability density of X and Y is given by + 0<x<1 and 0 <y< 2 otherwise a) Verify that this is a joint probability density function. b) Find P(x >Y). o) Find Pſy > for< d) Find Cov(X,Y). e) Find the correlation coefficient of X and Y (Pxy).
1. The joint density function is given by (a) Is this a valid joint probability density function? (b) Find Cov (Yi, 2) (c) Find BYi-3Y2) and VartYi-3Y2). 1. The joint density function is given by (a) Is this a valid joint probability density function? (b) Find Cov (Yi, 2) (c) Find BYi-3Y2) and VartYi-3Y2).
2. Suppose that Y and Y2 are continuous random variables with the joint probability density function (joint pdf) a) Find k so that this is a proper joint pdf. b) Find the joint cumulative distribution function (joint cdf), FV1,y2)-POİ уг). Be y, sure it is completely specified! c) Find P(, 0.5% 0.25). d) Find P (n 292). e) Find EDY/ . f) Find the marginal distributions fiv,) and f2(/2). g) Find EM] and E[y]. h) Find the covariance between Y1...