continuous random variables:
- construction of probability density functions from non-negative functions of a real variable
- specification of probability distributions for continuous random variables using probability density functions
- calculation and interpretation of mean, 𝜇, variance, 𝜎^2, and standard deviation of a continuous random variable and their use
- standard normal distribution, N(0, 1), and transformed normal distributions, N(𝜇, 𝜎^2), as examples of a probability distribution for a continuous random variable
- effect of variation in the value(s) of defining parameters on the graph of a given probability density function for a continuous random variable
- calculation of probabilities for intervals defined in terms of a random variable, including conditional probability (the cumulative distribution function may be used but is not required)
