Random Variable in probability theory is defined as follows: Assuming you have variables Xi where i is an integer ie: i=1,2,3.......n a variable Xi is called a random variable iff(if and only iff) and random selection yields a variable Xi for i=1,2.........,n with the same likelihood of appearance. i.e prob(X=Xi)=1/n
No.
The marginal probability distribution function.
Random variables is a function that can produce outcomes with different probability and random variates is the particular outcome of a random variable.
It is a variable that can take a number of different values. The probability that it takes a value in any given range is determined by a random process and the value of that probability is given by the probability distribution function.It is a variable that can take a number of different values. The probability that it takes a value in any given range is determined by a random process and the value of that probability is given by the probability distribution function.It is a variable that can take a number of different values. The probability that it takes a value in any given range is determined by a random process and the value of that probability is given by the probability distribution function.It is a variable that can take a number of different values. The probability that it takes a value in any given range is determined by a random process and the value of that probability is given by the probability distribution function.
Zero.
Yes. It is a continuous variable. As used in probability theory, it is an example of a continuous random variable.
In probability theory, the expectation of a discrete random variable X is the sum, calculated over all values that X can take, of : the product of those values and the probability that X takes that value. In the case of a continuous random variable, it is the corresponding integral.
It depends on what the random variable is, what its domain is, what its probability distribution function is. The probability that a randomly selected random variable has a value between 40 and 60 is probably quite close to zero.
No. The probability that a continuous random variable takes a specific value is always zero.
No.
That depends on the rules that define the random variable.
The marginal probability distribution function.
Random variables is a function that can produce outcomes with different probability and random variates is the particular outcome of a random variable.
A probability density function can be plotted for a single random variable.
The answer depends on the probability distribution function for the random variable.
It is a variable that can take a number of different values. The probability that it takes a value in any given range is determined by a random process and the value of that probability is given by the probability distribution function.It is a variable that can take a number of different values. The probability that it takes a value in any given range is determined by a random process and the value of that probability is given by the probability distribution function.It is a variable that can take a number of different values. The probability that it takes a value in any given range is determined by a random process and the value of that probability is given by the probability distribution function.It is a variable that can take a number of different values. The probability that it takes a value in any given range is determined by a random process and the value of that probability is given by the probability distribution function.
The Greek word "kurtosis", when translated to English, means the probability theory of any measure of the "peakedness" of a real valued random variable.