Given below is a bivariate distribution for the random variables and y. f(x, y) = 0.2 50 0.5 0.3 30 40 V 80 50 60

Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
Section: Chapter Questions
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Given below is a bivariate distribution for the random variables and y.
f(x,y) x
0.3
a. Compute the expected value and the variance for and y.
x+y
E(x) =
E(y) =
Var(z) =
Var(y) =
b. Develop a probability distribution for 2+ y (to 2 decimals).
130
80
38
61
76
169
f(x + y)
.3
0.2
.5
0.5
* >*
100
c. Using the result of part (b), compute E(x + y) and Var(x + y)
50
30
40
y
80
50
60
Transcribed Image Text:Given below is a bivariate distribution for the random variables and y. f(x,y) x 0.3 a. Compute the expected value and the variance for and y. x+y E(x) = E(y) = Var(z) = Var(y) = b. Develop a probability distribution for 2+ y (to 2 decimals). 130 80 38 61 76 169 f(x + y) .3 0.2 .5 0.5 * >* 100 c. Using the result of part (b), compute E(x + y) and Var(x + y) 50 30 40 y 80 50 60
80
100
c. Using the result of part (b), compute E(x+y) and Var(x + y).
.5
E(x+y)=
Var(x + y) =
469
d. Compute the covariance and correlation for 2 and y. If required, round your answers to two decimal places.
99
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.2
Covariance =
Correlation
The random variables and y are positively related
e. The variance of the sum of a and y is bigger than
By how much?
Var(x+y) is greater than Var(x) + Var(y) by twice the covariance
Partially Correcti
.98
* >
the sum of the individual variances.
Transcribed Image Text:80 100 c. Using the result of part (b), compute E(x+y) and Var(x + y). .5 E(x+y)= Var(x + y) = 469 d. Compute the covariance and correlation for 2 and y. If required, round your answers to two decimal places. 99 Hide Feedback .2 Covariance = Correlation The random variables and y are positively related e. The variance of the sum of a and y is bigger than By how much? Var(x+y) is greater than Var(x) + Var(y) by twice the covariance Partially Correcti .98 * > the sum of the individual variances.
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