**Probability Theory Explained**

Probability theory is the likelihood of a certain event or outcome of the event, to understand probability one needs to understand risk and the associated risk that is implied within the outcome. In academic realms probability theory is a branch of mathematics concerned with the analysis of sporadically charged phenomenon.

The very reason why probability, much like betting and casino games, have always captured the imagination of the public is due to the fact that no random event or action can be predicted before it happens. With more than one possible outcome, the outcome itself is left completely up to chance.

**Probability In Games Of Chance**

In games of chance the interpretation of probabilities as relative frequencies can be studied in order to assess a group capture event class. Basic games of chance involving coins, cards, dice and roulette wheels can provide clarity on the fundamental foundations of probability theory.

The one feature unique to all games of chance is the fact that no one single outcome can be predicted with complete conviction unlike looking at historical factors influencing Caulfield Cup betting at the races.

The only kind of estimation or educated guess, like that in games of chance can be made from a collection of results taken from tested runs. These tests show signs of regularity, hinting at specific outcomes dominance over and above any other.

Within these tests the regularity never points to one outcome, neither does it not. The trial runs simply gather data and loosely base a premise on the data gathered within the tests.

For example; The Coin Toss Test. In a coin toss where heads is directly opposed to tails, heads versus tails implies a 50 per cent probability ratio between the two sides, purely because there are only two possible outcomes.

**Probability Tested **

The probability, which exists by throwing two dice on to a table, has thirty-six possible outcomes. An ordered pair can represent each outcome. This ordered pair here is A. B. Now A.B assumes one of the dice values ranging from 1,2,3,4,5,6 and represents the faces on each individual dice.

In this probability test, it is important that each dice is thought of in distinguishable terms, by realising each individual dice as a different coloured dice, this allows for variances in the outcome, i.e. 1.2 is different to 2.1.

Now the event or outcome from all possible outcomes, by throwing the pair of dice on to the table and generating a number equating to six, consists of five potential outcomes. These five potential outcomes may take the form of a 1&5, 2&4, 3&3, 4&2 or 5&1.

**A Simple Formula For Probability**

If the probability of an event can be defined as the percentage based possibility of the defined outcome, then one can formulate probability with a simple equation.

To formulate probability, the probability of event X is the number of ways event X can occur, divided by the total number of possible outcomes to event X.

**Example Of Probability In Cards**

You have a standard deck of playing cards. What is the probability of drawing a face card?

Well to calculate the probability of this outcome the equation is as follows:

There are four suits with three face cards in each suit. This is represented as 3×4, which equates to 12 face cards out of a total of 52 playing cards.

Therefore; 12/52 = 3/13 = 23.1 % probability.