Ch 12; Introducing Probability Flashcards

1
Q

Chance Behavior

A

Unpredictable short term but has a regular, predictable pattern long-term.

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2
Q

Randomness

A

Individual outcomes uncertain but still a regular pattern/ distribution of outcomes in a large number of repetitions

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3
Q

Probability

A

Probability of any outcome of a random phenomenon is the proportion of times the outcome would occur in a very long series of repetitions

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4
Q

Probability Model

A

A mathematical description of a random phenomenon consisting of 2 parts; a sample space (s) & a way of assigning probabilities to events

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5
Q

Sample Space (s)

A

Set of all possible outcomes

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6
Q

Event

A

An outcome/ set of outcomes of a random phenomenon (A subset of sample space)

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7
Q

Probability of Any Event Equation

A

(# of ways the event could occur) / (Total # of outcomes in the sample space)

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8
Q

Probability Rules (4)

A

1) The probability P(A) of any event (A) satisfies
0≤ P(A)≤ 1
2) If s is the sample space in a probability model then P(s)=1
3)Two events A & B are disjoint if they have no outcomes in common, so can never occur together.
If A & B are disjoint; P(A or B) = P(A) + P(B)
4) For any event A, P(A does not occur) = 1 - P(A)

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9
Q

Finite/Discrete Probability Model

A

A probability model w/ a finite sample space (All probabilities must be #s b/w 0 & 1, as well as add to 1)

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10
Q

Probability of any Event in a Finite Probability Model

A

The sum of the probabilities of the outcomes making up the event

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11
Q

Continuous Probability Models

A

Assigns probabilities as areas under a density curve. The area under the curve & b/w any range of values is the probability of an outcome in that range

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12
Q

Uniform Distribution

A

Same height over all intervals

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13
Q

Example of Continuous Probability Model

A

Normal Distributions

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14
Q

Random Variable

A

A variable whose value is a numerical outcome of a random phenomenon

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15
Q

Probability Distribution of a Random Variable X

A

Tells us what value X can take & how to assign probabilities to those values

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16
Q

2 Types of Random Variables

A

Finite & Continuous Random Variable

17
Q

Finite Random Variable

A

Has a finite list of possible outcomes (ex. 1,2,3,4,5)

18
Q

Continuous Random Variable

A

Can take on any value in an interval, w/ probabilities given as areas under a density curve

19
Q

Personal Probability

A

Of an outcome is a number b/w 0 & 1 that expresses an individuals judgement of how likely that outcome is.