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Lectures prepared by: Elchanan Mossel Yelena Shvets Introduction to probability Stat 134 FAll 2005 Berkeley Follows Jim Pitman’s book: Probability Section.

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Presentation on theme: "Lectures prepared by: Elchanan Mossel Yelena Shvets Introduction to probability Stat 134 FAll 2005 Berkeley Follows Jim Pitman’s book: Probability Section."— Presentation transcript:

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2 Lectures prepared by: Elchanan Mossel Yelena Shvets Introduction to probability Stat 134 FAll 2005 Berkeley Follows Jim Pitman’s book: Probability Section 5.2

3 Joint Desity The density function f(x,y) for a pair of RVs X and Y is the density of probability per area of (X,Y) near (x,y).

4 Joint Desity

5 Densities single variable bivariate norm

6 Probabilities single variable bivariate norm P(X  a) = s - 1 a f(x)dx P(X  a,Y · b) = s - 1 a s - 1 b f(x) dx dy

7 x x P(X=x, Y=y)=P(x,y) Infinitesimal & Point Probability Continuous Discrete

8 x x Probability of Subsets Continuous Discrete

9 Constraints Continuous Discrete Non-negative: Integrates to 1:

10 Constraints Continuous Discrete Marginals: \ Independence: for all x and y.

11 Expectations ContinuousDiscrete Expectation of a function g(X): Covariance:

12 Expectations ContinuousDiscrete Expectation of a function g(X): Covariance:

13 Joint Distributions (X,Y) » Uniform{-1<X<1, X 2 · Y · 1}, 1 1 0 Find the joint density f(x,y) such that P(X 2 dx, Y 2 dy) = f(x,y)dx dy. Find the marginals. Are X,Y independent? Compute: E(X),E(Y), P(Y<X); X’ » X, Y’ » Y & independent, find P(Y’<X’)? Questions: y=x 2 y=1 0

14 Joint Distributions (X,Y) » Uniform{-1<X<1, X 2 · Y · 1}. 1 1 0 Find the joint density f(x,y) such that P(X 2 dx, Y 2 dy) = f(x,y)dx dy. Solution: Since the density is uniform f(x,y) = c =1/area(D). D f(x,y) = ¾ for (x,y) 2 D; f(x,y) = 0 otherwise y=x 2 y=1 0

15 Joint Distributions (X,Y) » Uniform{-1<X<1, X 2 · Y · 1}, f(x,y) = ¾. y=x 2 1 1 0 0 Find the marginals. y=1

16 Constraints Continuous Discrete Marginals: \

17 Joint Distributions (X,Y) » Uniform{-1<X<1, X 2 · Y · 1}, f(x,y) = ¾. y=x 2 1 1 0 0 Solution: Find the marginals. y=1

18 Joint Distributions (X,Y) » Uniform{-1<X<1, X 2 · Y · 1} y=x 2 1 1 0 y=1 Are X,Y independent? 0

19 Constraints Continuous Discrete Independence: for all x and y.

20 Joint Distributions (X,Y) » Uniform{-1<X<1, X 2 · Y · 1} y=x 2 1 1 0 Solution: y=1 Are X,Y independent? X,Y are dependent! 0

21 Joint Distributions (X,Y) » Uniform{-1<X<1, X 2 · Y · 1} y=x 2 1 1 0 Solution: y=x 0 Compute: E(X),E(Y), P(Y<X); A D-A

22 Joint Distributions 1 1 0 Solution: y=x 0 A X’ » X, Y’ » Y & X’,Y’ are independent, find P(Y’<X’)? We need to integrate this density over the indicated region A = the subset of the rectangle [-1,1] £ [0,1] where y<x.

23 Joint Distributions X = Exp(1), Y = Exp(2), independent Find the joint density f(x,y) such that P(X 2 dx, Y 2 dy) = f(x,y)dx dy. Compute: P(X<2Y); Questions: f Y 0 X

24 Joint Distributions X = Exp(1), Y = Exp(2), independent Find the joint density. Questions: f Y 0 X Since X and Y are independent, we multiply the densities for X and Y For x ≥ 0, y ≥ 0

25 Joint Distributions X = Exp(1), Y = Exp(2), independent Questions: f Y 0 X We need to 1: Find the region x>2y Compute: P(X>2Y) X Y y = x/2

26 Joint Distributions X = Exp(1), Y = Exp(2), independent Questions: f Y 0 X We need to 2: Integrate over the region Compute: P(X>2Y) X Y X = 2Y


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