Two criminal cases/law suits are randomly assigned to one or more of three lawyers in a big law fir Ben and Cameron (abbreviated to A,B and C). Let X₁ denote the number of contracts assigned to X₂ denote the number of contracts assigned to Ben. For some reason, completely beyond my contro not interested in Cameron's escapades. 1. Find the joint probability function of X₁ and X₂.

Holt Mcdougal Larson Pre-algebra: Student Edition 2012
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ISBN:9780547587776
Author:HOLT MCDOUGAL
Publisher:HOLT MCDOUGAL
Chapter11: Data Analysis And Probability
Section11.8: Probabilities Of Disjoint And Overlapping Events
Problem 2C
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sub question 4 and 5 please

Two criminal cases/law suits are randomly assigned to one or more of three lawyers in a big law firm: Anna,
Ben and Cameron (abbreviated to A,B and C). Let X₁ denote the number of contracts assigned to Anna and
X₂ denote the number of contracts assigned to Ben. For some reason, completely beyond my control, we are
not interested in Cameron's escapades.
1. Find the joint probability function of X₁ and X₂.
2. Find the marginal distribution ƒx₁ (7₁) of X₁ and the marginal distribution fx₂ (₂) of X₂.
3. Are X and Y independent? Give reasons.
4. Calculate the expected values E(X), E(Y) and the variances V ar(X), Var(Y).
5. Calculate the covariance Cov(X₁, X2) of X₁ and X₂ . Hint: Use definition
-
Cov(X,Y) = E[(X – E(X))(Y – E(Y))]ΣΣ(x − E(X))(y − E(y) * f (x, y))
х у
Transcribed Image Text:Two criminal cases/law suits are randomly assigned to one or more of three lawyers in a big law firm: Anna, Ben and Cameron (abbreviated to A,B and C). Let X₁ denote the number of contracts assigned to Anna and X₂ denote the number of contracts assigned to Ben. For some reason, completely beyond my control, we are not interested in Cameron's escapades. 1. Find the joint probability function of X₁ and X₂. 2. Find the marginal distribution ƒx₁ (7₁) of X₁ and the marginal distribution fx₂ (₂) of X₂. 3. Are X and Y independent? Give reasons. 4. Calculate the expected values E(X), E(Y) and the variances V ar(X), Var(Y). 5. Calculate the covariance Cov(X₁, X2) of X₁ and X₂ . Hint: Use definition - Cov(X,Y) = E[(X – E(X))(Y – E(Y))]ΣΣ(x − E(X))(y − E(y) * f (x, y)) х у
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