Joint probability distribution

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SUMMARY

The discussion revolves around the joint probability distribution of two random variables, X and Y. The calculations for P(X + Y ≤ 4) involve summing specific probabilities, yielding a result based on the provided joint distribution. The marginal probability distributions are derived as f1(1) = 0.3, f1(2) = 0.25, f1(3) = 0.45, and f2(1) = 0.35, f2(2) = 0.3, f2(3) = 0.35. The conditional probability P(X < 2|Y = 2) is determined to be f(1,2) = 0.05, and it is concluded that X and Y are not independent since f(1,1) does not equal f1(1)f2(1).

PREREQUISITES
  • Understanding of joint probability distributions
  • Knowledge of marginal probability distributions
  • Familiarity with conditional probability
  • Concept of independence in probability theory
NEXT STEPS
  • Study the properties of joint probability distributions
  • Learn how to compute marginal distributions from joint distributions
  • Explore conditional probability and its applications
  • Investigate the criteria for independence of random variables
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Students studying probability theory, statisticians analyzing joint distributions, and educators teaching concepts of marginal and conditional probabilities.

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Homework Statement


4. Let X and Y have the joint probability distribution

Screen Shot 2015-10-19 at 5.45.15 PM.png

(a) Find P(X +Y ≤ 4).

(b) Find the marginal probability distributions f1(x) and f2(y).

(c) Find P(X < 2|Y = 2).

(d) Are X and Y independent?

The Attempt at a Solution


a) f(1,1) + f(1,2) + f(1,3) + f(2,1) + f(2,2) + f(3,1)

b) f1(1) = .1 + .05 + .15 = .3
f1(2) = .1 + .05 + .1 = .25
f1(3) = .15 + .2 + .1 = .45

f2(1) = .35
f2(2) = .3
f2(3) = .35

c) f(1,2) = .05

d) they are independent if f(x,y) = f1(x)f2(y) for all x and y
f(1,1) = .1 f1(1)f2(1) = .3(.35) = .105
they are not independent .is this correct?
 
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It looks right to me.
 
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thanks!
 

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