probability and stats Flashcards
(31 cards)
Explain P(A)P(B) in plain English
The probability of independent events A and B occurring.
Explain P(A and B) in plain English
The probability of events A and B occurring together.
And rule for independence:
P(A and B) = ?
P(A and B) = P(A)* P(B)
assumes A, B are independent events
And rule for dependence
P(A and B) = ?
P(A and B) = P(A) * P(B | A)
P(A and B) = P(B) * P(A | B)
assumes A, B are dependent events
Are independent events are mutually exclusive?
No! Common fallacy. Independent events are NOT mutually exclusive!
Or rule (generalized to mutually exclusive and non-mutually exclusive events): P(a or b) =
P(a) + P(b) - P(a and b)
Or rule for mutually exclusive events:
P(a or b) = ?
P(a or b) = P(a) + P(b)
What’s the definition of conditional probability?
P(A | B) = P(A and B) / P(B)
probability of A given that B occurred
(only valid when P(B) > 0)
P(B) is the total outcome space. You know B happened, so you’re in that space, hence it’s the denominator.
P(A | B) = 0.2
What is P(~A | B)?
P(~A | B) = 0.8
Realize that you’re summing over outcomes for A, not B!
Conditionalized version of Bayes theorem in the context of general background evidence E:
P(X | Y, E) = ?
P(X | Y, E) = P(X | E) * P(Y | X, E) / P(Y | E)
Conditionalized version of marginalization in the context of general background evidence E:
P(X | E) = ?
P(X | E) = sum over y of P(X, Y = y | E)
What does the following statement mean in plain english?
P(X | Y, E) = P(X|E)
X is conditionally independent of Y given E
What does the following statement mean in plain english?
P(Y | X, E) = P(Y | E)
X is conditionally independent of Y given E
What does the following statement mean in plain english?
P(X, Y | E) = P(X | E) P(Y | E)
X is conditionally independent of Y given E
Marginal independence: produce 2 other equivalent statements that imply each other:
P(X|Y) = P(X)
…
…
P(X|Y) = P(X)
P(Y|X) = P(Y)
P(X, Y) = P(X) P(Y)
All imply each other.
Conditional independence: produce 2 other equivalent statements that imply each other:
P(X|Y, E) = P(X | E)
…
…
P(X|Y, E) = P(X | E)
P(Y | X, E) = P(Y | E)
P(X, Y | E) = P(X | E) P(Y | E)
what’s a synonym for disjoint?
mutually exclusive
what’s a synonym for mutually exclusive?
disjoint
what does it mean when A is disjoint from B?
A and B cannot happen at the same time
How do you determine if events A and B are mutually exclusive?
P(A and B) = 0
Can you have a events A, B that are independent and disjoint of each other?
If at least one of the events has zero probability, then the two events can be mutually exclusive and independent simultaneously. Let A be the empty set, for example, and let B be any event. Then they are mutually exclusive (because their intersection is empty) and they are independent (because the probability of their intersection is equal to the product of their individual probabilities, which is zero).
However, if both events have non-zero probability, then they cannot be mutually exclusive and independent simultaneously. “Mutually exclusive” implies that the intersection of the two events has zero probability, but the events themselves have non-zero probabilities, so the product of their probabilities cannot be zero.
Can you have a events A, B that are independent and NOT disjoint of each other?
Yes, of course
Apply conditionalized bayes rule (flip C and D):
P(C|A,B,D) = …
Background evidence = A, B
P(C | A,B,D) = P(D | C,A,B) * P(C | A, B) / P(D | A, B)
What is a prior probability?
a probability w/o conditions
e.g. P(A)