The mean of a discrete probability distribution is also called the Expected Value.
It is the set of values that a variable can take together with the probability or frequency distribution for those values.
It depends on the parameter - the mean of the distribution.
Nothing since it is impossible. No event can have 5 as the probability of success.
The mean and standard deviation do not, by themselves, provide enough information to calculate probability. You also need to know the distribution of the variable in question.
The mean of a binomial probability distribution can be determined by multiplying the sample size times the probability of success.
The mean of a discrete probability distribution is also called the Expected Value.
with mean and standard deviation . Once standardized, , the test statistic follows Standard Normal Probability Distribution.
It is a value around which the distribution lies.
Zero.
Yes.
yes
They are probability distributions!
It is a probability distribution in which the probability of the random variable being in any interval on one side of the mean (expected value) is the same as for the equivalent interval on the other side of the mean.
The mean of a sample is a single value and so its distribution is a single value with probability 1.
Uniform probability can refer to a discrete probability distribution for which each outcome has the same probability. For a continuous distribution, it requires that the probability of the outcome is directly proportional to the range of values in the desired outcome (compared to the total range).
50%