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Can two events be mutually exclusive and independent simultaneously?
No, two events cannot be mutually exclusive and independent simultaneously. Mutually exclusive events cannot occur at the same time, meaning the occurrence of one event excludes the possibility of the other. In contrast, independent events are defined such that the occurrence of one event does not affect the probability of the other occurring. Therefore, if two events are mutually exclusive, the occurrence of one event implies that the other cannot occur, which contradicts the definition of independence.
What is the measure of how likely an event will occur?
Probability is the measure of how likely an event is. ... The probability of event A is the number of ways event A can occur divided by the total number of possible.
Is the probability assigned to an event that is certain not to occur is 1.0?
No; if it is certain not to occur the probability is 0.
If the probability that an event will occur is 1 then the event is certain to occur?
Yes, the probabilty scale is from one to zero so is the probability is 0 it will definitely not occur
What is a mathematical chance that an event will occur?
Probability of success is a mathematical chance that an event will occur.
Probability of an event occurring to the probability that it won't occur?
These events are complementary. Let P(A) = probability event will occur. Then the probability it will not occur is: 1 - P(A).
If two events are mutually exclusive what is the probability that both occur at the same time?
The probability is 0. Consider the event of tossing a coin . The possible events are occurrence of head and tail. they are mutually exclusive events. Hence the probability of getting both the head and tail in a single trial is 0.
If two events are independent the probability that both occur is?
That probability is the product of the probabilities of the two individual events; for example, if event A has a probability of 50% and event B has a probability of 10%, the probability that both events will happen is 50% x 10% = 5%.
What is the probability of an event occurring to the probability that it will not occur?
The probability that an event will occur plus the probability that it will not occur equals 1.
What does unlikely mean in probability?
In common usage, unlikely means a low probability of occurrence. But as a term in mathematics, an unlikely event is not rigorously defined as a "low number" is subjective. Certainly, in a comparative sense, i.e. event A is less likely to occur than event B, we can state that the probability of occurrence of A is less than B.
What will a likelihood that a particular event will occur?
The likelihood of an occurrence is called its probability.Other terms associated with probability are chance, risk, and possibility.
What is the likelihood that particular events will occur?
The likelihood of an occurrence is called its probability.Other terms associated with probability are chance, risk, and possibility.
Probability of an impossible event is?
an impossible event has a probability of 0, it will never occur a certain event has a probability of 1, it will always occur
What is the relationship between the probability of an event's occurrence and the probability that it will not occur?
% chance to occur + % chance to not occur = 100% Expressed in decimals, 40% chance to occur + 60% chance to not occur = 100%. .40 + .60 = 1.00 More detailed answer: === === Probability of event occurrence versus failure to occur First, probabilities are expressed as decimals or fractions with values between zero and one, with zero representing no possibility of an event's occurrence, and one representing the certainty of occurrence. For example, the probability of flipping a heads with one flip of a fair coin is 0.5 or 1/2. The probability of rolling a snake-eye with one roll of one fair die is 0.167 or 1/6. The probability of pulling the Ace of spades out of regular deck of shuffled cards (without the jokers) is 0.0192 or 1/52. The probability of pulling a heart -- any heart -- out of the same deck (assuming the Ace of spades was put back in) is 0.25 or 13/52. Remember, a probability must always be between 0 and 1. If you ever do a probability calculation and get a result greater than one, you screwed up. Second, the probability of any event's failure to occur is one minus the probability of the event's occurrence. So, if the probability of rolling a snake-eye with one fair die is 0.167, then the probability of NOT rolling a snake-eye is 1 - 0.167 = 0.833. (Or 1 - 1/6 = 5/6.) The probability of NOT drawing a heart from a deck of 52 cards is 1 - 0.25 = 0.75. (Or 1 - 1/4 = 3/4). == ==
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.
What is the probability of an event?
How likely it is for an event to occur.
What do you mean by probability?
Probability is a measure of the expectation that an event will occur or a statement is true. Probabilities are given a value between 0 (will not occur) and 1 (will occur).[1] The higher the probability of an event, the more certain we are that the event will occur.
