1 sandwich 2 sandwiches d drinks. The joint distribution on the right summarizes e number of sandwiches (X) and drinks (Y) purchased customers. Complete parts (a) through (f). 0.35 0.20 Y 0.10 0 0.25 0.10 Find the expected value and variance of the number of sandwiches. X) = 1.55 Var(X) = 0.2475 ype integers or decimals.) Find the expected value and variance of the number of drinks. Y) = 1.55 Var(Y) = 0.4475 ype integers or decimals.) Find the correlation between X and Y. (Hint: You might find the calculations easier if you use the alternative pression for the covariance.) Orr(X,Y)= ound to three decimal places as needed.) 1 drink 2 drinks 3 drinks
1 sandwich 2 sandwiches d drinks. The joint distribution on the right summarizes e number of sandwiches (X) and drinks (Y) purchased customers. Complete parts (a) through (f). 0.35 0.20 Y 0.10 0 0.25 0.10 Find the expected value and variance of the number of sandwiches. X) = 1.55 Var(X) = 0.2475 ype integers or decimals.) Find the expected value and variance of the number of drinks. Y) = 1.55 Var(Y) = 0.4475 ype integers or decimals.) Find the correlation between X and Y. (Hint: You might find the calculations easier if you use the alternative pression for the covariance.) Orr(X,Y)= ound to three decimal places as needed.) 1 drink 2 drinks 3 drinks
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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1 sandwich 2 sandwiches
Customers at a fast-food restaurant buy both sandwiches
and drinks. The joint distribution on the right summarizes
the number of sandwiches (X) and drinks (Y) purchased
by customers. Complete parts (a) through (f).
1 drink
0.35
0.20
Y
2 drinks
0.25
0.10
0
3 drinks
0.10
(a) Find the expected value and variance of the number of sandwiches.
E(X)= 1.55 Var(X) = 0.2475
(Type integers or decimals.)
(b) Find the expected value and variance of the number of drinks.
E(Y) = 1.55 Var(Y) = = 0.4475
(Type integers or decimals.)
(c) Find the correlation between X and Y. (Hint: You might find the calculations easier if you use the alternative
expression for the covariance.)
Corr(X,Y)=
(Round to three decimal places as needed.)
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