How do we model a single trial with exactly two outcomes, and what are its mean and variance?
Use the Bernoulli distribution to model a single two-outcome trial and find its mean and variance
WACE Year 12 Mathematics Methods Unit 3 the Bernoulli distribution: a single success-or-failure trial, its probability function, mean p and variance p times one minus p, and its role as the building block of the binomial, with a worked example.
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What this dot point is asking
SCSA Unit 3 introduces the Bernoulli distribution as the simplest discrete model: one trial, two outcomes. This dot point asks you to state its distribution and derive its mean and variance, which then generalise directly to the binomial distribution. It supports questions in both examination sections.
The Bernoulli model
A Bernoulli trial has exactly two outcomes, conventionally labelled success and failure. The random variable records for success and for failure.
Examples include a single coin toss (success = heads), one inspected item (success = defective), or one penalty kick (success = goal).
Mean and variance
Because takes only the values and , the mean and variance follow directly from the definitions of expected value and variance.
The mean is
For the variance, note that since and , so . Then
Link to the binomial distribution
A binomial random variable counts the number of successes in independent Bernoulli trials, each with the same . Adding independent Bernoulli variables gives the binomial, which is why the binomial mean and variance are simply times the Bernoulli values. Understanding the single-trial case makes the binomial formulae intuitive rather than memorised.