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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). == ==
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When do you use poisson probability?
When you have independent events which have a constant probability of occurrence over an interval of space or time.
What is the relationship between conditional probability and the concept of statistical independence?
If events A and B are statistically indepnedent, then the conditional probability of A, given that B has occurred is the same as the unconditional probability of A. In symbolic terms, Prob(A|B) = Prob(A).
What are the requirements for Poisson distribution?
Independent events with a constant probability of occurrence over a fixed interval of time (or space).
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.
What is the or rule in probability?
Given two events, A and B, the probability of A or B is the probability of occurrence of only A, or only B or both. In mathematical terms: Prob(A or B) = Prob(A) + Prob(B) - Prob(A and B).
What events are such that the occurrence of one does not change the probability of other events?
Independent events.
What is the definition of dependent events?
Two events are dependent if the outcome or occurrence of the first affects the outcome or occurrence of the second so that the probability is changed.
When do you use poisson probability?
When you have independent events which have a constant probability of occurrence over an interval of space or time.
Relationship between Exponential and Poisson Distributions?
Poisson distribution shows the probability of a given number of events occurring in a fixed interval of time. Example; if average of 5 cars are passing through in 1 minute. probability of 4 cars passing can be calculated by using Poisson distribution. Exponential distribution shows the probability of waiting times between occurrences of events. If we use the same example; probability of a car coming in next 40 seconds can be calculated by using exponential distribution. -Poisson : probability of x times occurrence -Exponential : probability of waiting times between events.
If probability of occurrence of event A is p and that of occurrence of event B is q then what is probability that both the events do not occur?
The answer depends on whether A and B can occur together, that is, if they are mutually exclusive.
What does probability show us?
It shows us the likelihood of the occurrence of specified events.
Is it true that two dependent events can have the same probability of occurring?
Yes, it is possible for two dependent events to have the same probability of occurring. The probability of an event is dependent on the outcomes of other events, and it is influenced by the relationship between these events. So, it is conceivable for two dependent events to have equal probabilities.
What is the difference between dependent and independent events in terms of probability?
What is the difference between dependant and independent events in terms of probability
What is the relationship between conditional probability and the concept of statistical independence?
If events A and B are statistically indepnedent, then the conditional probability of A, given that B has occurred is the same as the unconditional probability of A. In symbolic terms, Prob(A|B) = Prob(A).
What is independent events in probability concepts?
The occurrence of one event does not affect the occurrence of the other event. Take for example tossing a coin. The first toss has no affect on the outcome of the second toss, so these events are independent.
What are the requirements for Poisson distribution?
Independent events with a constant probability of occurrence over a fixed interval of time (or space).
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.
