Answer:
1
Explanation:
First, take a look at this.
We also know that we can cancel out a lot of fractions.
1. DISCRETE RANDOM VARIABLES
1.1. Definition of a Discrete Random Variable. A random variable X is said to be discrete if it can
assume only a finite or countable infinite number of distinct values. A discrete random variable
can be defined on both a countable or uncountable sample space.
1.2. Probability for a discrete random variable. The probability that X takes on the value x, P(X=x),
is defined as the sum of the probabilities of all sample points in Ω that are assigned the value x. We
may denote P(X=x) by p(x) or pX(x). The expression pX (x) is a function that assigns probabilities
to each possible value x; thus it is often called the probability function for the random variable X.
1.3. Probability distribution for a discrete random variable. The probability distribution for a
discrete random variable X can be represented by a formula, a table, or a graph, which provides
pX (x) = P(X=x) for all x. The probability distribution for a discrete random variable assigns nonzero
probabilities to only a countable number of distinct x values. Any value x not explicitly assigned a
positive probability is understood to be such that P(X=x) = 0.