POINT 6.2
UNDERSTAND
DISCRETE PROBABILITY DISTRIBUTIONS
DISCRETE PROBABILITY DISTRIBUTIONS
A random variable is a variable whose value dependes on the outcome of a random event. They are denoted using upper
case letter such as X or Y
Probability Distributions
A discrete probability distribution fullly describes all the values that a discrete random variable can take along with their
associated probiablities. This can be given in a TABLE or FUNCTION
How to draw a probability distribution
table
Decide how many times the situations can take place? such as
can we have 0 roses, 3 roses?
Find the probability of each situation
How do you solve ?
Do the probabilities add up to 1?
If K is not a possible value then P(X=k)=0 ?
Identify all possible values, x, that X can take which
satisfy x ≤ k
Add together alltheir corresponding probabilities
Check list
It basically means P(X=x) is equal to
the relative frequency of each
particular value of X. Note that the
sum of probabilities of X has to add
up to 1
Check if the elements are being replaced or not. If
the elements are not replaced then you CANNOT be
doing binomial, geometrical and probability
distribution but you can do permutations and
combinations and other probability!
Exam Tip
So for line 1: This basically
proves that a probability less
than k, more than k and k
should add up to 1 as it’s the
total probabilities of that
particular situation
So for line 2: It is basically
stating that the probability of
X greater than k is equal to 1 -
the probability of X less than
or equal to k
So for line 3 it’s basically
saying the probability of X
being greater or equal to k is
equal to 1- the probability of X
being less than k
