the concepts of a random variable (discrete and continuous), Bernoulli trials and probability distributions, the parameters used to define a distribution and properties of probability distributions and their graphs
U34.AoS4.2
discrete random variables:
- specification of probability distributions for discrete random variables using graphs, tables and probability mass functions
- calculation and interpretation of mean, 𝜇, variance, 𝜎^2, and standard deviation of a discrete random variable and their use
- Bernoulli trials and the binomial distribution, Bi(𝑛, 𝑝), as an example of a probability distribution for a discrete random variable
- effect of variation in the value(s) of defining parameters on the graph of a given probability mass function for a discrete random variable
- calculation of probabilities for specific values of a random variable and intervals defined in terms of a random variable, including conditional probability
U34.AoS4.6
the conditions under which a Bernoulli trial or a probability distribution may be selected to suitably model various situations
