Financial Risk Manager Classroom Training| What is Discrete Probability Distribution? Video Lecture | Risk Management: An Essential Training - Management

simply learn your pace your place
financial risk manager frm part 1 of the
frm exam covers the fundamental tools
and techniques used in risk management
and the theories that underlie their use
discrete probability distributions
before we go into detail about discrete
probability distribution let us recall
what a random variable is from our
learning in the previous sessions a
random variable say X represents a
numerical value with each outcome of a
probability distribution a random
variable can either be discrete or
continuous a discrete random variable is
a finite countable value for example the
number of people going to a soccer match
a random variable is continuous if it
has unaccountable values for example the
waiting time at McDonald's on a given
day agenda in this session we will learn
mainly about three different types of
discrete probability distributions
Bernoulli distribution by nominal
distribution and Poisson distribution in
the end we'll make a comparative study
of these distributions Bernoulli
distribution this distribution
represents the success probability as P
and the failure probability as Q equals
1 minus P with a value of zero the
Bernoulli distribution is calculated to
evaluate the probability of whether a
company will default or survive in a
given time when the solvency of a
company is assessed the outcome will
either be successful which is denoted
with a value of one or failure with a
value of zero to make it simpler in the
case of the Bernoulli distribution the
event that is taken into consideration
to evaluate the probable outcome will
always have two possibilities for
example when a coin is tossed the
probable outcome will be heads or tails
that is P equals 1 over 2 and Q equals 1
over to a Bernoulli distribution is a
simplest model and is considered to be
the foundation of all other discrete
distributions phenomenal distribution
a binomial distribution is an event or
trial that will only have two possible
outcomes the two possible outcomes can
either be success or failure for example
as mentioned in the previous paragraph
when a fair coin is tossed the outcome
will either be heads or tails for an
event to be by nominal the following
assumptions