b) Discrete Probability distribution consists of the values a random variable can assume and the corresponding probabilities of the values. a) All probabilities must between 0 and 1 b) The sum of the probabilities must add up to 1. Continuous RANDOM VARIABLE – The number of values that X can assume is INFINITE.Click to see full answer. Hereof, what are the requirements for a distribution to be a probability distribution?A probability density function must satisfy two requirements: (1) f(x) must be nonnegative for each value of the random variable, and (2) the integral over all values of the random variable must equal one.Also Know, how do you find the expected value? The expected value (EV) is an anticipated value for an investment at some point in the future. In statistics and probability analysis, the expected value is calculated by multiplying each of the possible outcomes by the likelihood each outcome will occur and then summing all of those values. Regarding this, what Makes a probability distribution? A probability distribution is a function that describes the likelihood of obtaining the possible values that a random variable can assume. In other words, the values of the variable vary based on the underlying probability distribution.What makes a discrete probability distribution valid?To be a valid discrete probability distribution, we need: the sum of the probabilities of all the possible values of the random variable to be 1, i.e., X Pr ( X = x ) = 1 ; the probabilities of each possible value of the random variable to lie between 0 and 1, i.e., 0 ≤ Pr ( X = x ) ≤ 1 .