1.1 Definitions
Definition 1.1 (Sample space) A sample space, often denoted by S, is the set of all possible outcomes of a random trial or experiment.
Definition 1.2 (Random) An event is random if its outcome is uncertain, and is (at least partially) due to chance.
Definition 1.3 (Variable) A variable changes its value from situation to situation, or from realisation to realisation. That is, the value varies.
Example 1.1 (Variables; sample space) The country in which people were born is a variable; it varies from person to person.
The sample space is rather large, but we could use this more restricted sample space: S={Australia,UK,China,Canada,Elsewhere}.
Definition 1.4 (Random variable) A random variable (often written as ) is a ‘rule’ associating a number with each outcome in a sample space S.
Mathematically: a rv is a function whose domain is the sample space S, and whose range is a set of real numbers.
Example 1.2 (Random variables) We could (arbitrarily) define a rv, say C, such that C={1for Australia2for UK3for China4for Canada5for elsewhere
A rv is often denoted by a capital letter (for example, X), and lower case letters used (for example, x) for the value that the rv takes.
So Pr means “the probability that the rv X takes a particular value x.”
Sometimes, we just write x for both when there is no ambiguity.
Example 1.3 (Random variables) Suppose we are examing delicate light bulbs, and keep trying them until we find one that fails.
The rv X can be defined as ‘the number of bulbs we try until we find one that fails.’
The sample space is S = \{1, 2, 3, \dots\}. Notice that there’s no upper limit in theory.
If we write \Pr(X > 4), this means ‘the probability that more than four trials are needed to find a bulb that fails.’
Example 1.4 (Random variables) The heights of adult Australian females in centimetres is a random variable, say H.