3. Probability: Probability
Definition of Probability
In everyday language, probabilities are often described as percentages. In statistics, however, all probabilities are expressed as a number between #0# and #1#.
"The probability that a fair coin comes up head is #50\%#" translates to "the probability that a fair coin comes up head is #0.5#" in statistics.
A probability of #0# or a probability of #1# follow these rules:
- An event that has no chance of occurring has a probability of #0#
- e.g. the probability that someone is born on February 30th is #0#.
- An event that is certain to occur has a probability of #1#
- e.g. if today is Thursday, then the probability that tomorrow is Friday is #1#.
The greater the probability of an event, the more likely it is that the event will occur.
Probability
Definition
Probability is the likelihood that an event will occur, quantified as a number between #0# and #1#.
If the probability of an event #A# occurring is #p#, this is written as: #\mathbb{P}(A)=p#.
For an experiment in which several different outcomes are possible, the probability of any specific outcome is defined as a fraction or proportion of all the possible outcomes.
Formula
\[\mathbb{P}(A) = \cfrac{\text{number of outcomes classified as }A}{\text{total number of possible outcomes}}\]
Rules
- The probability of any event A, #\mathbb{P}(A)#, is always greater than or equal to #0# and less than
or equal to #1#:
\[0\leq \mathbb{P}(A) \leq 1\] - The sum of the probabilities of all possible outcomes must equal #1#. That is, if the sample space is #\Omega#, then
\[\sum_{\text{all }x \text{ in }\Omega}\mathbb{P}(x)=1\]
