Chapter 10 Probability. Experiments, Outcomes, and Sample Space Outcomes: Possible results from...

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Chapter 10

Probability

Experiments, Outcomes, andSample Space

• Outcomes: Possible results from experiments in a random phenomenon

• Sample Space: Collection of all possible outcomes– S = {female, male}– S = {head, tail}– S = { 1, 2, 3, 4, 5, 6}

• Event: Any collection of outcomes– Simple event: event involving only one outcome– Compound event: event involving two or more outcomes

Basic Properties of Probability

• Probability of an event always lies between 0 & 1

• Sum of the probabilities of all outcomes in a sample space is always 1

• Probability of a compound event is the sum of the probabilities of the outcomes that constitute the compound event

1)(0 EP

1)( EP

Probability

• Equally Likely Events

• Probability as Relative Frequency

– Relative frequency <> Probability (Law of large numbers)

• Subjective Probability

nEP i

1)(

n

f

n

occursAtimesofNoAP

.)(

Combinatorial Probability

• Using combinatorics to calculate possible number of outcomes

• Fundamental Counting Principle (FCP): Multiply each category of choices by the number of choices

• Combinations: Selecting more than one item without replacement where order is not important

• Examples– Lottery– Dealing cards: 3 of a kind

Marginal Probability

• The probability of one variable taking a specific value irrespective of the values of the others (in a multivariate distribution)

• Contingency table: a tabular representation of categorical data

Purchased Warranty

Did Not Purchase Warranty

Total

Bought a used car 26 17 43

Bought a new car 73 35 108

Total 99 52 151

Conditional Probability

• The probability of an event occurring given that another event has already occurred

Purchased Warranty

Did Not Purchase Warranty

Total

Bought a used car 26 17 43

Bought a new car 73 35 108

Total 99 52 151

Conditional Probability

Purchased Warranty

Did Not Purchase Warranty

Total

Bought a used car 26 17 43

Bought a new car 73 35 108

Total 99 52 151

Event A Event B P(A) P(B|A)

Used carWarranty

43/151=.284826/43=.6047

No Warranty 17/43=.3953

New carWarranty

108/151=.715273/108=.6759

No Warranty 35/108=.3241

Conditional Probability

Purchased Warranty

Did Not Purchase Warranty

Total

Bought a used car 26 17 43

Bought a new car 73 35 108

Total 99 52 151

Event B Event A P(B) P(A|B)

WarrantyUsed Card

99/151=.655626/99=.2626

New Car 73/99=.7374

No WarrantyUsed Card

52/151=.344417/52=.3269

New Car 35/52=.6731

Joint of Events

• Set theory is used to represent relationships among events. In general, if A and B are two events in the sample space S, then– A union B (AB) = either A or B occurs or both occur

– A intersection B (AB) = both A and B occur

– A is a subset of B (AB) = if A occurs, so does B

– A' or Ā = event A does not occur (complementary)

Probability of Union of Events

• Mutually Exclusive Events: if the occurrence of any event precludes the occurrence of any other events

• Addition Rule

n

ii

n

ii EPEP

11

)()(

)()()()( 212121 EEPEPEPEEP

)()()()(

)()()()(

ABCPBCPACPABP

BPBPAPCBAP

Probability of Union of Events

Purchased Warranty

Did Not Purchase Warranty

Total

Bought a used car 26 17 43

Bought a new car 73 35 108

Total 99 52 151

• Probability of (bought a used car) or (purchased warrant)

Equity 50% Equity < 50% Total

Cr. Rating 700 87 133 220

Cr. Rating < 700 53 727 108

Total 140 860 1000

• Probability of (Cr. Rating 700) or (Equity 50%)

Probability of Mutually Exclusive Events

Purchased Warranty

Did Not Purchase Warranty

Total

Bought a used car 26 17 43

Bought a new car 73 35 108

Total 99 52 151

• Probability of (purchased warrant) or (Did not purchased warrant)

Equity 50% Equity < 50% Total

Cr. Rating 700 87 133 220

Cr. Rating < 700 53 727 108

Total 140 860 1000

• Probability of (Cr. Rating 700) or (Cr. Rating < 700)

Probability of Complementary Events

• Complementary Events: When two mutually exclusive events contain all the outcomes in the sample space

0.1)()()()( APAPAorAPAAP

Probability of Intersection of Events

• Independent Events: Event whose occurrence or non-occurrence is not in any way influenced by the occurrence or non-occurrence of another event

• Multiplication Rule

n

ii

n

ii EPEP

11

)()(

)|()()|()()( BAPBPABPAPBAP

)()|( APBAP

)()()( BPAPBAP

)()|( BPABP

Probability of Intersection of Events

Purchased Warranty

Did Not Purchase Warranty

Total

Bought a used car 26 17 43

Bought a new car 73 35 108

Total 99 52 151

Event A Event B P(A) P(B|A) P(AB)

Used carWarranty

43/151=.284826/43=.6047 .1722

No Warranty 17/43=.3953 .1126

New carWarranty

108/151=.715273/108=.6759 .4834

No Warranty 35/108=.3241 .2318

Warranty

No Warranty

.6759

.3241

Warranty

No Warranty

.6047

.3953

Used Car

New Car

.7152

Probability of Intersection of Events

.2848

.1722

.1126

.4834

.2318

Probability of Intersection of Events

Purchased Warranty

Did Not Purchase Warranty

Total

Bought a used car 26 17 43

Bought a new car 73 35 108

Total 99 52 151

Event B Event A P(B) P(A|B) P(AB)

WarrantyUsed Card

99/151=.655626/99=.2626 .1722

New Car 73/99=.7374 .4834

No Warranty

Used Card52/151=.3444

17/52=.3269 .1126

New Car 35/52=.6731 .2318

Used Car

New Car

.2626

.7374

Used Car

New Car

.3269

.6731

.3444

Probability of Intersection of Events

.6556

.1722

.1126

.4834

.2318

Warranty

No Warranty