A distribution of a statistic calculated from all possible samples of a given size from a population.

The sampling distribution of the sample mean approaches a normal distribution as the sample size increases, regardless of the original population's distribution.

The standard deviation of a sampling distribution; it measures the variability of the sample statistic.

Variables that can only take on a finite number of values or a countable number of values.

Variables that can take on any value within a given range.

A measure that describes a characteristic of an entire population; it's a fixed, true value.

A measure that describes a characteristic of a sample; it's an estimate of the population parameter.

$E(X) = \sum x_i \cdot P(x_i)$

$\sigma = \sqrt{\sum (x_i - \mu)^2 \cdot P(x_i)}$

Discrete: Finite or countable values, e.g., number of students | Continuous: Any value within a range, e.g., height.

Parameters: Describe populations, fixed values | Statistics: Describe samples, estimates of parameters.