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.
The probability increases.The probability increases.The probability increases.The probability increases.
That depends on the rules that define the random variable.
Yes.
It depends on the parameter - the mean of the distribution.
Random variables is a function that can produce outcomes with different probability and random variates is the particular outcome of a random variable.
A random variable is a variable that can take different values according to a process, at least part of which is random.For a discrete random variable (RV), a probability distribution is a function that assigns, to each value of the RV, the probability that the RV takes that value.The probability of a continuous RV taking any specificvalue is always 0 and the distribution is a density function such that the probability of the RV taking a value between x and y is the area under the distribution function between x and y.
No. The probability that a continuous random variable takes a specific value is always zero.
No.
The probability increases.The probability increases.The probability increases.The probability increases.
That depends on the rules that define the random variable.
The area under the pdf between two values is the probability that the random variable lies between those two values.
The marginal probability distribution function.
A random variable is a variable which can take different values and the values that it takes depends on some probability distribution rather than a deterministic rule. A random process is a process which can be in a number of different states and the transition from one state to another is random.
A probability density function can be plotted for a single random variable.
The answer depends on the probability distribution function for the random variable.
A probability density function assigns a probability value for each point in the domain of the random variable. The probability distribution assigns the same probability to subsets of that domain.