Types Of Events In Probability

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					              Types Of Events In Probability
Types Of Events In Probability

The theory of probability was developed with the study of games of chance such as playing
with dice and cards. Along with games we also face uncertainty in different phases of life like
business, projects, economy and in many other day to day activities of life.

In all these areas we face uncertainty and so probability plays a great role in these areas of
life. When we talk about the subset of any sample space, it is called an event.

If there are n elements in the set of the space then their exist 2^n number of events of that
particular set. Events can be of different types based on their quality. Here are different types
of events in probability:

Probability is the science of calculating the likelihood that an event will occur. The probability
expresses the number of times an event has occurred over the total amount of times the event

An example given by the business department of Clayton State University is: if a company
receives 80 supply batches, but 15 are rejected, the chance the next batch will be rejected is
15:80, or a 1:16 probability.
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Mutually Exclusive Events :- A mutually exclusive event is a probability that is always zero.
This is because the probability cannot be produced since both variables cannot happen
logically in reality.

Mutually exclusive events are considered deterministic probabilities, meaning the probability
will always happen. Only bizarre situations or the rules governing the variables being
overturned can result in the probability not equaling zero.

Certified Quality Engineers, a company that test preps engineers for certification exams, gives
the probability example of a 25-year-old becoming President of the United States. This
probability is impossible, since constitutionally, no 25-year-old can become the President of
the United States.

Classical Events :- The classical approach is a method of probability assigned to see how
often an event will happen. It is called the classical approach because it is seen as the central
purpose of probability: calculating the likelihood of an event.

Unlike a deterministic event, the classical approach tries to find the probabilistic outcome in a
set. An example presented by Certified Quality Engineers is: how many games will there be in
a sports championship series like baseball.

Most championship series games have seven games at maximum. However, the team that
wins the championship only needs to win four games.

The mathematics department at the University of Illinois demonstrates this by stating that
winning the first four games is a 1/8 probability, winning after five games is a 1/4 probability,
and winning in the sixth or seventh game is a 5/16 probability.

Relative Frequency Events :- Relative frequency events are events that have a determined
variable of time compared to what happened during that time. Relative frequency is
deterministic in nature, since there is a finite number of variables being used.
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For example, a relative frequency event would be how many times a character says a catch
phrase on a television program.

The program's variable may be a season or the entire series of the program. Either way, there
is only so many recorded times when the catch phrase is said. If there are 100 episodes and
the catch phrase was said in 80 episodes, the probability is 80/100, or 4/5 of the time.

Subjective Events :- Subjective events are events in probability that contain random
variables assigned by an individual. For example, if a meteorologist wants to inform the public
on the likelihood of rain in the forecast, she must calculate variables she determines are

There are endless variable sets to assign in a subjective event, since the person determines
what is a valuable variable. The meteorologist might not think air pressure, for example, is a
factor to include in a probability calculation, but another meteorologist might.                                                    Page No. : ­ 3/4
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