Provided the random variable can take only finitely many, equally spaced values, you can write one in terms of the other. For details see the paper by Ales Cerny entitled "Introduction to Fast Fourier Transform in finance".
The Poisson distribution is discrete.
They are probability distributions!
Half the discrete unit.
A discrete probability distribution is defined over a set value (such as a value of 1 or 2 or 3, etc). A continuous probability distribution is defined over an infinite number of points (such as all values between 1 and 3, inclusive).
It is a function that gives the probabilities associated with the discrete number of values that a random variable can take.
The binomial probability distribution is discrete.
The Poisson distribution is discrete.
They are probability distributions!
No. Normal distribution is a continuous probability.
The mean of a discrete probability distribution is also called the Expected Value.
Half the discrete unit.
If X has any discrete probability distribution then the sum of a number of observations for X will be normal.
A discrete probability distribution is defined over a set value (such as a value of 1 or 2 or 3, etc). A continuous probability distribution is defined over an infinite number of points (such as all values between 1 and 3, inclusive).
Normal distribution is the continuous probability distribution defined by the probability density function. While the binomial distribution is discrete.
1.
the empirical rules of probablility applies to the continuous probability distribution
A Bernoulli distribution is a discrete probability distribution which takes value 1 with success probability p and value 0 with failure probability q = 1 - p.