and the variance for x and y.

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter10: Statistics
Section10.1: Measures Of Center
Problem 9PPS
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Question
(b) Develop a probability distribution for x + y.
x + y
130
80
100
f(x + y)
(c) Using the result of part (b), compute E(x + y) and Var(x + y).
E(x + y) =
Var(x + y) =
(d) Compute the covariance and correlation for x and y. (Round your answer for correlation to two decimal places.)
covariance
correlation
Are x and y positively related, negatively related, or unrelated?
The random variables x and y are ---Select---
(e) Is the variance of the sum of x and y bigger, smaller, or the same as the sum of the individual variances? Why?
The variance of the sum of x and y is ---Select--- ✓the sum of the variances by two times the covariance, which occurs whenever two random variables are ---Select---
Transcribed Image Text:(b) Develop a probability distribution for x + y. x + y 130 80 100 f(x + y) (c) Using the result of part (b), compute E(x + y) and Var(x + y). E(x + y) = Var(x + y) = (d) Compute the covariance and correlation for x and y. (Round your answer for correlation to two decimal places.) covariance correlation Are x and y positively related, negatively related, or unrelated? The random variables x and y are ---Select--- (e) Is the variance of the sum of x and y bigger, smaller, or the same as the sum of the individual variances? Why? The variance of the sum of x and y is ---Select--- ✓the sum of the variances by two times the covariance, which occurs whenever two random variables are ---Select---
Given below is a bivariate distribution for the random variables x and y.
f(x, y) x y
0.3
0.5
0.2
50 80
30 50
40 60
(a) Compute the expected value and the variance for x and y.
E(X) =
E(y) =
Var(x) =
Var(y) =
Transcribed Image Text:Given below is a bivariate distribution for the random variables x and y. f(x, y) x y 0.3 0.5 0.2 50 80 30 50 40 60 (a) Compute the expected value and the variance for x and y. E(X) = E(y) = Var(x) = Var(y) =
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