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If two events are mutually exclusive and collectively exhaustive what is the probability that one or the other occurs?
If A and B are mutually exclusive, P(A or B)=P(A) + P(B) They both cannot occur together. For example: A die is rolled. A = an odd number; B= number is divisible by 2. P(A or B) = 1/3 + 1/3 = 2/3
When two events are independent the probability that one event occurs in no way affects the probability of the other event occurring true or false?
It is true.
How can you state and illustrate the addition multiplication Theorem of Probability?
Addition Theorem The addition rule is a result used to determine the probability that event A or event B occurs or both occur. ; The result is often written as follows, using set notation: : ; where: : P(A) = probability that event A occurs : P(B) = probability that event B occurs : = probability that event A or event B occurs : = probability that event A and event B both occur ; For mutually exclusive events, that is events which cannot occur together: : = 0 ; The addition rule therefore reduces to : = P(A) + P(B) ; For independent events, that is events which have no influence on each other: : ; The addition rule therefore reduces to : ; Example ; Suppose we wish to find the probability of drawing either a king or a spade in a single draw from a pack of 52 playing cards. ; We define the events A = 'draw a king' and B = 'draw a spade' ; Since there are 4 kings in the pack and 13 spades, but 1 card is both a king and a spade, we have: : = 4/52 + 13/52 - 1/52 = 16/52 ; So, the probability of drawing either a king or a spade is 16/52 (= 4/13).MultiplicationTheorem The multiplication rule is a result used to determine the probability that two events, A and B, both occur. The multiplication rule follows from the definition of conditional probability. ; The result is often written as follows, using set notation: : ; where: : P(A) = probability that event A occurs : P(B) = probability that event B occurs : = probability that event A and event B occur : P(A | B) = the conditional probability that event A occurs given that event B has occurred already : P(B | A) = the conditional probability that event B occurs given that event A has occurred already ; For independent events, that is events which have no influence on one another, the rule simplifies to: : ; That is, the probability of the joint events A and B is equal to the product of the individual probabilities for the two events.
Two events are independent if the probability of one event is influenced by whether or not the other event occurs?
True
What is the difference between relative frequency approximation of probability and the classical approach to probability?
Relative frequency approximation is conducting experiments and counting the number of times the event occurs divided by the total number of events. The classical approach is determine the number of ways the event can occur divided by the total number of events.
If two events are collectively exhastive what is the probability that one or or the other occurs?
1.
If two events are mutually exclusive and collectively exhaustive what is the probability that one or the other occurs?
If A and B are mutually exclusive, P(A or B)=P(A) + P(B) They both cannot occur together. For example: A die is rolled. A = an odd number; B= number is divisible by 2. P(A or B) = 1/3 + 1/3 = 2/3
If two events are mutually exclusive what is the probability that one or the other occurs?
Add the probabilities of the two events. If they're not mutually exclusive, then you need to subtract the probability that they both occur together.
When two events are independent the probability that one event occurs in no way affects the probability of the other event occurring true or false?
It is true.
How can you state and illustrate the addition multiplication Theorem of Probability?
Addition Theorem The addition rule is a result used to determine the probability that event A or event B occurs or both occur. ; The result is often written as follows, using set notation: : ; where: : P(A) = probability that event A occurs : P(B) = probability that event B occurs : = probability that event A or event B occurs : = probability that event A and event B both occur ; For mutually exclusive events, that is events which cannot occur together: : = 0 ; The addition rule therefore reduces to : = P(A) + P(B) ; For independent events, that is events which have no influence on each other: : ; The addition rule therefore reduces to : ; Example ; Suppose we wish to find the probability of drawing either a king or a spade in a single draw from a pack of 52 playing cards. ; We define the events A = 'draw a king' and B = 'draw a spade' ; Since there are 4 kings in the pack and 13 spades, but 1 card is both a king and a spade, we have: : = 4/52 + 13/52 - 1/52 = 16/52 ; So, the probability of drawing either a king or a spade is 16/52 (= 4/13).MultiplicationTheorem The multiplication rule is a result used to determine the probability that two events, A and B, both occur. The multiplication rule follows from the definition of conditional probability. ; The result is often written as follows, using set notation: : ; where: : P(A) = probability that event A occurs : P(B) = probability that event B occurs : = probability that event A and event B occur : P(A | B) = the conditional probability that event A occurs given that event B has occurred already : P(B | A) = the conditional probability that event B occurs given that event A has occurred already ; For independent events, that is events which have no influence on one another, the rule simplifies to: : ; That is, the probability of the joint events A and B is equal to the product of the individual probabilities for the two events.
Two events are independent if the probability of one event is influenced by whether or not the other event occurs?
True
Which of these occurs when workers collectively agree to stop working?
strike
What is the difference between relative frequency approximation of probability and the classical approach to probability?
Relative frequency approximation is conducting experiments and counting the number of times the event occurs divided by the total number of events. The classical approach is determine the number of ways the event can occur divided by the total number of events.
What is the formula in finding the probability of an event?
If you can enumerate the outcome space into equally likely events, then it is the number of outcomes that are favourable (in which the event occurs) divided by the total number of outcomes.
The what of an event is how many times it occurs?
Probability of an event is how many times it occurs.
What is experimental probability vs theoretical probability?
Theoretical probability is what should occur (what you think is going to occur) and experimental probability is what really occurs when you conduct an experiment.
What is a risk management?
A Risk is an uncertain event or condition that if it occurs, has a positive or negative effect on a Project's Objectives. Risk Management literally refers to the management of the Projects Risk. However, the official definition is: Risk Management is the act of increasing the probability & impact of positive events and decreasing the probability & impact of adverse events within a project.
