Karteikarten
Lecture 3
Karten in diesem Stapel (16)
- 1What is probability?The chance that a particular event will occur
Probability value 0 = no chance
Probability value 1 = certain - 2What is an experiment?A process that produces a single outcome whose result cannot be predicted with certainty
- 3What is a sample space?The collection of all outcomes that can result from a selection, decision, or experiment
E.g. All 6 faces of a die, all 52 cards in a deck, etc - 4What is an event of interest?A collection of experimental outcomes
- 5What is mutually exclusive?If the occurrence of one event precludes the occurrence of the other event
- 6What are independent events?If the occurrence of one event in no way influences the probability of the other event occuring
- 7What are the 3 types of probability assessment?1. Classical
2. Relative frequency
3. Subjective - 8Classical probabilityPr(E) = (Number of ways E can occur)
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Total number of possible outcomes - 9Relative frequency probabilityDefined as the number of times an event occurs divided by the total number of times an experiment is performed in a large number of trials (historical)
Pr(E) = Number of times E occurred
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N - 10Subjective probabilityDefined by reflecting a decision maker's states of mind regarding the chances that the particular event will occur
-Represents a person's belief that an event will occur
-Only approximate guide to the future - 11OddsOdds for:
Pr(E)
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1 - Pr(E)
Odds against:
1 - Pr(E)
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Pr(E) - 12Complement ruleThe complement of an event E is the collection of all possible outcomes not contained in the event E.
- 13Addition rule for any two events *Not mutually exclusivePr(E or A) = Pr(E) + Pr(A) - Pr(E and A)
-Not for mutually exclusive events, they do not overlap in venn diagram so we wouldn't need to remove them. In this case, we do - 14Addition rule for mutually exclusive eventsPr(E or A) = Pr(E) + Pr(A)
- 15Conditional probabilityDefined as the probability that an event will occur given that some other event has already happened
Pr(E | A) = Pr(E and A) / P(E)
*Over P(E) because our sample space is reduced to that as we MUST include it - 16Probability of two independent eventsPr(E and A) = Pr(E) x Pr(A)
Informationen
- Beschreibung
- Statistics Karteikarten am Lecture 3, erstellt von Jacob Lewis am 19/03/2019.
- Erstellt von
- Jacob Lewis · Mär 2019
- Aktualisiert
- 19 Mär 2019
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- 2
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