Probability lec Flashcards
Result of an observation or experiment, or the descriptor or some potential outcome.
EVENT
A subset of the set of all possible outcomes of a probabilistic experiment.
EVENT
In probability studies, events are represented by
uppercase letters (A, B, etc.).
The measure of the likelihood of an event happening.
* Measures the certainty of an event.
PROBABILITY
The intersection of two events is read as
“both A and B”.
INTERSECTION (A∩B)
. If either A and B are not fulfilled, this event, this intersection is not counted/valued for.
INTERSECTION (A∩B)
The union of two events is read as
“Either A or B, or
both A and B”.
UNION (A∪B)
The complement of an event is read as “Not A”. this means that the non-fulfillment or the converse/opposite event of A is the trigger for this operation.
COMPLEMENT (Ac or Ā)
In the Venn diagram below, the area within the rectangle box represents all the outcomes
sample space
Represents all the outcomes that could possibly occur,
sample space
sample space symbol
P(S)=1
An event that can never occur and has a probability of zero, whereas most events have probabilities between the value 0 and 1.
NULL EVENT
NULL EVENT symbol
A∩Ac=∅
When two events are mutually exclusive, the additive rule of probability states that the probability that either of the two events will occur is equal to the sum of the probabilities of the individual events.
ADDITIVE RULE OF PROBABILITY
ADDITIVE RULE OF PROBABILITY formula
P(A∪B) = P(A) + P(B)
This is the type of probability wherein the probability of one event is directly influenced by the probability of another event.
CONDITIONAL PROBABILITY
CONDITIONAL PROBABILITY symbol
P(A|B)
The multiplicative rule of probability states that the probability that two events A and B will both occur is equal to the probability of B multiplied by the conditional probability of A given that B has already occurred.
MULTIPLICATIVE RULE OF PROBABILITY
MULTIPLICATIVE RULE OF PROBABILITY symbol
P(A∩B) = P(B) P(A|B)
P(A∩B) = P(A) P(B|A)
P(A∩B) = P(A) P(B)
A fundamental rule relating marginal probabilities to conditional probabilities
TOTAL PROBABILITY
It expresses the total probability of an outcome which can be realized via several distinct events.
TOTAL PROBABILITY
set of events that all amount to the sum of 1 – meaning that there are no other possible outcomes, and it must fall under one of the categories.
exhaustive
exhaustive symbol
S = A1∪A2∪A3
This is a function wherein you want to compare the probability of occurrence of an event between two groups.
RELATIVE RISK (RR)
This describes the probability or chance of a member of the exposed group to develop the outcome in relation to the probability of a membernof the unexposed group to develop the same outcome.
RELATIVE RISK (RR)
formula for relative risk
P (outcome | exposed) / P(outcome |unexposed)
f an event takes place with probability p, then the odds in favor of the event are the probability that the event will occur divided by the probability the event will not occur or ___
odds ratio, p/(1-p) to 1.
This is a function wherein you want to calculate for the odds in favor of the event.
odds ratio
The ___ represents the odds that an outcome will occur given a particular exposure, compared to the odds of the outcome occurring in the absence of that exposure.
The OR
formula for odd
P (outcome | exposed)/[1-P(outcome |exposed)] over P (outcome | unexposed)/[1-P(outcome |unexposed)]
