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The calculation is equal to the sum of their probabilities less the probability of both events occuring.
If two events are mutually exclusive then the combined probability that one or the other will occur is simply the sum of their respective probabilities, because the chance of both occurring is by definition zero.
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When to use cumulative binomial probability?
When the event of interest is a cumulative event. For example, to find the probability of getting three Heads in 8 tosses of a fair coin you would use the regular binomial distribution. But to find the probability of up to 3 Heads you would use the cumulative distribution. This is because Prob("up to 3") = Prob(0 or 1 or 2 or 3) = Prob(0) + Prob(1) + Prob(2) + Prob(3) since these are mutually exclusive.
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.
A number is chosen 1 to 25 find the probabillity of selecting a number greater than 18?
Probability is ratio of the events you want over the total number of events. There are 7 numbers greater than 18 and you have 25 total options, so your probability is 7/25 or 28%.
How do you find the probability of the complement of an event?
The probability of the complement of an event, i.e. of the event not happening, is 1 minus the probability of the event.
How can you find a probability expressed as a percentage from a punnett square?
You can find probability form a Punnett square by turning fractions into percents
What is principle of additivity?
The principle of additivity states that the probability of the union of two mutually exclusive events is equal to the sum of their individual probabilities. This means that when events are mutually exclusive (cannot both occur at the same time), their probabilities can be added together to find the probability of either event occurring.
How do you find the probability of multiple events?
The answer depends on whether or not the events are independent.
How do you find the probability of disjoint events?
Multiply the possible outcomes of the events in the disjoint events
How do you find the probability of two distincve events?
It depends on whether or not the events are independent.
How don you find the answers to simple independent events?
you find the probability
When to use cumulative binomial probability?
When the event of interest is a cumulative event. For example, to find the probability of getting three Heads in 8 tosses of a fair coin you would use the regular binomial distribution. But to find the probability of up to 3 Heads you would use the cumulative distribution. This is because Prob("up to 3") = Prob(0 or 1 or 2 or 3) = Prob(0) + Prob(1) + Prob(2) + Prob(3) since these are mutually exclusive.
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 flipping no heads when you flip three identical coins?
The probability of flipping one coin and getting tails is 1/2. In order to find the probability of multiple events occurring, you find the product of all the events. For 3 coins the probability of getting tails 3 times is 1/8 because .5 x .5 x .5 = .125 or 1/8.
How do you find the probability of an event followed by another event?
If the events are independent then you can multiply the individual probabilities. But if they are not, you have to use conditional probabilities.
Find the probability that in a family of 4 children will be a at least 1 boy and 3 girls?
There is no simple answer to the question because children's genders are not independent events. They depend on the parents' ages and their genes. However, if you assume that they are independent events then, given that the probability of a boy is approx 0.52, the answer is 0.2331.
How do you find the probability of 2 dependent events?
That will depends entirely on how the two events are related. For instance, there may be a weak correlation, or a strong correlation, between two probabilities. You really need more information, about how the events are related. There is no single simple rule.
A number is chosen 1 to 25 find the probabillity of selecting a number greater than 18?
Probability is ratio of the events you want over the total number of events. There are 7 numbers greater than 18 and you have 25 total options, so your probability is 7/25 or 28%.
