Unit 4 Flashcards

1
Q

What is empirical probability?

A

of successful trials / # total trials

This formula represents the likelihood of an event based on observed outcomes.

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2
Q

What does the Law of Large Numbers state?

A

More trials = closer to true probability

This law suggests that as the number of trials increases, the empirical probability will converge to the true probability.

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3
Q

What is a random process?

A

Any situation where we don’t know the outcome

Random processes are fundamental in probability theory as they involve uncertainty.

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4
Q

What is a sample space?

A

Set of all possible non-overlapping outcomes

The sample space encompasses every potential result of a random process.

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5
Q

How is the probability of an event E calculated?

A

P(E) = # of outcomes in favor of Event / Total # of outcomes in sample space

This formula quantifies the likelihood of event E occurring.

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6
Q

What is the range of probabilities?

A

Between 0 and 1

A probability of 0 indicates an impossible event, while a probability of 1 indicates a certain event.

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7
Q

What is the complement of an event?

A

The event not happening

The complement of event E is denoted as E^c, representing all outcomes where E does not occur.

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8
Q

What is the relationship between probability and repeated experiments?

A

Probability is defined through repeated experiments

This emphasizes that probability is not just a theoretical concept but is determined through actual trials.

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9
Q
A
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10
Q

What are mutually exclusive events?

A

Events that cannot occur at the same time.

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11
Q

What is the joint probability formula?

A

P (A and B) = P (A ∩ B)

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12
Q

What is the value of P (A and B) for mutually exclusive events?

A

P (A and B) = P (A ∩ B) = 0

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13
Q

How can you determine if P(A ∩ B) is mutually exclusive?

A

Create a 2-way table.

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14
Q

What is conditional probability?

A

The probability that an event will happen given that another event has occurred.

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15
Q

What does P(A | B) represent?

A

The probability of A given B.

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16
Q

P(A | B) = ?

A

P(A ∩ B) / P(B)

17
Q

Equation of independence

A

P(A ∩ B) = P(A) * P(B)