11 Probability Theory Flashcards

1
Q

Random experiment

A

A process leading to an uncertain outcome

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2
Q

Basic outcome

A

A possible outcome of a random experiment

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3
Q

Sample space

A

The collection of all possible outcomes of a random experiment

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4
Q

Event

A

Any subset of basic outcomes from the sample space

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5
Q

Set

A

A collection of objects

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6
Q

Elements

A

The objects in a set

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7
Q

Mutually exclusive events

A

When A and B have no basic outcomes in common A n B =0

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8
Q

Subset

A

When every element of A is also an element in B, A c B

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9
Q

Collectively exhaustive

A

If the union of events completely cover the sample space

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10
Q

Complement

A

The complement of an event A is the set of all basic outcomes in the sample space that don’t belong to A. Complement is denoted Ā

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11
Q

Probability

A

The chance that an uncertain event will occur

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12
Q

Probability postulates

A
  1. If A is any event in the sample space, then: 0<=P(A)<=1
  2. The probability of the event A is equal to the sum of all basic outcomes of event A
  3. The probability of at least one thing in the sample space will occur is P(S)=1
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13
Q

Addition rule

A

P(AuB)= P(A)+P(B)-P(AnB)

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14
Q

Addition rule if events A and B are collectively exhaustive

A

P(AuB)=1

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15
Q

Compliment rule

A

P(Ā)=1-P(A)

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16
Q

What is Conditional probability

A

The probability of one event occurring given that another event has occurred

17
Q

Equation for conditional probability of A given that B has occurred

A

P(A|B)= P(AnB)/P(B)

18
Q

Equation for conditional probability of B given that A has occurred

A

P(B|A)= P(AnB)/P(A)

19
Q

Multiplication rule

A
P(AnB)= P(A|B)P(B)
P(AnB)= P(B|A)P(A)
20
Q

Bayes’ theorem

A

P(A|B)= P(B|A)P(A)/P(B)

21
Q

What is statistical independence?

A

Two events are statistically independent if and only if
P(AnB)=P(A)P(B)
P(A|B)=P(A)

22
Q

Probability distribution

A

Lists all the possible outcomes of a random experiment snd the probability associated with each one

23
Q

What is the probability distribution determined by

A

The nature of the experiment not the data produced. E.g probability distribution of a coin would be 0.5 for heads and 0.5 for tails regardless of how many of each we get when we flip the coin 20 times