From a probability perspective fair means equal probability.
It means multiply, Probaility of A and B means probability of A multiplied by probability of B.
The mean of a binomial probability distribution can be determined by multiplying the sample size times the probability of success.
If you mean 43%, then the probability that it will not snow is 57%, 0.57 or 57/100.
The complement (not compliment) of the probability of event A is 1 minus the probability of A: that is, it is the probability of A not happening or "not-A" happening.The complement (not compliment) of the probability of event A is 1 minus the probability of A: that is, it is the probability of A not happening or "not-A" happening.The complement (not compliment) of the probability of event A is 1 minus the probability of A: that is, it is the probability of A not happening or "not-A" happening.The complement (not compliment) of the probability of event A is 1 minus the probability of A: that is, it is the probability of A not happening or "not-A" happening.
From a probability perspective fair means equal probability.
Read the introduction to probability and probability measures at StatLect.com
It means multiply, Probaility of A and B means probability of A multiplied by probability of B.
The mean of a binomial probability distribution can be determined by multiplying the sample size times the probability of success.
The answer depends on the underlying distribution.
The significance of the mean of a probability distribution is that it is the most probably thing to happen. The mean is the average of a set of values. If it is the average of a probability distribution, it is the most probable part.
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Dependent probability is the probability of an event which changes according to the outcome of some other event.
It is the probability of an event calculated from repeated trials of an experiment.
If you mean 43%, then the probability that it will not snow is 57%, 0.57 or 57/100.
The mean of a discrete probability distribution is also called the Expected Value.
A z-value by itself, has nothing to do with level of confidence.A z-value can be used to calculate probabilities of observing a result that is at least as far from the mean. That probability measure can be used to calculate the level of confidence but you need to be careful about using the one-tailed or two-tailed measures - as appropriate.A z-value by itself, has nothing to do with level of confidence.A z-value can be used to calculate probabilities of observing a result that is at least as far from the mean. That probability measure can be used to calculate the level of confidence but you need to be careful about using the one-tailed or two-tailed measures - as appropriate.A z-value by itself, has nothing to do with level of confidence.A z-value can be used to calculate probabilities of observing a result that is at least as far from the mean. That probability measure can be used to calculate the level of confidence but you need to be careful about using the one-tailed or two-tailed measures - as appropriate.A z-value by itself, has nothing to do with level of confidence.A z-value can be used to calculate probabilities of observing a result that is at least as far from the mean. That probability measure can be used to calculate the level of confidence but you need to be careful about using the one-tailed or two-tailed measures - as appropriate.