It is always non-negative.
The sum (or integral) over all possible outcomes is 1.
The mean must be 0 and the variance must be 1.
They are probability distributions!
(1) That the probabilities lie between 0 and 1. (2) The sum of all probabilities of the distribution sum up to 1.
Independent events with a constant probability of occurrence over a fixed interval of time (or space).
A bell shaped probability distribution curve is NOT necessarily a normal distribution.
The requirements are that there are repeated trials of the same experiment, that each trial is independent and that the probability of success remains the same.
The mean must be 0 and the variance must be 1.
The normal distribution, also known as the Gaussian distribution, has a familiar "bell curve" shape and approximates many different naturally occurring distributions over real numbers.
They are probability distributions!
(1) That the probabilities lie between 0 and 1. (2) The sum of all probabilities of the distribution sum up to 1.
Independent events with a constant probability of occurrence over a fixed interval of time (or space).
No. Normal distribution is a continuous probability.
Yes. When we refer to the normal distribution, we are referring to a probability distribution. When we specify the equation of a continuous distribution, such as the normal distribution, we refer to the equation as a probability density function.
The statement is true that a sampling distribution is a probability distribution for a statistic.
how do i find the median of a continuous probability distribution
None. The full name is the Probability Distribution Function (pdf).
A bell shaped probability distribution curve is NOT necessarily a normal distribution.