Independent Probability Question

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tomtom690
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Homework Statement


Hello, I just want to know if I am going about this the right way.
A and B are outcomes of a random experiment in a sample space [tex]\Omega[/tex] such that [tex]\Omega[/tex] = A[tex]\cup[/tex]B. P(A) = 0.8 and P(B) = 0.5 Study if A and B, A and B[tex]^{c}[/tex], A[tex]^{c}[/tex] and B, and A[tex]^{c}[/tex] and B[tex]^{c}[/tex] are independent outcomes. Also, evaluate P(A[tex]\cup[/tex]B[tex]^{c}[/tex]) etc.


Homework Equations





The Attempt at a Solution


For the first three, I have used the same reasoning. I shall give an example of A and B[tex]^{c}[/tex].
Since [tex]\Omega[/tex] = A[tex]\cup[/tex]B then A[tex]\cup[/tex]B[tex]^{c}[/tex]=A
Now, let x = P(A[tex]\cup[/tex]B[tex]^{c}[/tex])=P(A)+P(B[tex]^{c}[/tex])-P(A[tex]\cap[/tex]B[tex]^{c}[/tex])

Now if A and B[tex]^{c}[/tex] are independent, then their intersection is the same as multiplying them together. So P(A[tex]\cap[/tex]B[tex]^{c}[/tex]) = 0.8*0.5 = 0.4
This means that P(A[tex]\cup[/tex]B[tex]^{c}[/tex]) = 0.9 [tex]\neq[/tex] P(A) = 0.8, so they are not independent.

However I am having difficulty applying this reasoning (if correct!) to the final one. And then the evaluation part seems too easy, as I have already said in this working out what they are equal to.

Thanks.
 
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[tex]P(A^c \cap B^c) = 1 - P(A \cup B) = 0[/tex]

whereas

[tex]P(A^c)P(B^c) = (0.2)(0.5) \neq 0[/tex]

so [itex]A^c[/itex] and [itex]B^c[/itex] are not independent.
 
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As for the other questions, I calculated

[tex]P(A \cup B) = P(A) + P(B) - P(A \cap B)[/tex]

so

[tex]1 = 0.8 + 0.5 - P(A \cap B)[/tex]

which means that

[tex]P(A \cap B) = 0.3[/tex]

Now use

[tex]P(A) = P(A \cap B) + P(A \cap B^c)[/tex]

to establish that

[tex]P(A \cap B^c) = 0.5[/tex]

which disagrees with your calculation.

[Edit] Oh wait, I see what you did. Yes, I think your way is OK, too.

If you use my calculation, you would observe that

[tex]P(A)P(B^c) = (0.8)(0.5) = 0.4[/tex]

which does not equal [itex]P(A \cap B^c)[/itex], so [itex]A[/itex] and [itex]B^c[/itex] are not independent.

You can then calculate

[tex]P(A \cup B^c) = P(A) + P(B^c) - P(A \cap B^c) = 0.8[/tex]
 
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