Population parameter

A population parameter is a numerical characteristic of an entire population, such as its mean, proportion, or variance. It is fixed for a defined population but is often unknown and estimated from sample data.

Statistical population: A defined set of individuals or units about which statistical conclusions are made. A parameter describes a characteristic of this entire defined set.
Parameter estimation: The use of sample data to infer unknown values of population parameters. It turns observed sample information into estimates of population characteristics.
Statistical parameter: A fixed numerical quantity that specifies a feature of a statistical model or population. The broader idea includes model parameters as well as population characteristics.
Survey sampling: Methods for selecting and analyzing samples to describe a target population. Survey estimates aim to recover population parameters from selected respondents.
Sample statistic: A numerical summary calculated from observations in a sample. Unlike a population parameter, it varies across samples and can be computed from observed data.
Estimator: A rule or formula that maps sample data to an estimate of an unknown quantity. An estimator is the procedure used to approximate a population parameter.
Random variable: A quantity whose value is determined by a random process and described by a probability distribution. A parameter is fixed in the model, whereas sample-derived statistics can be random.
Margin of error: A measure of sampling uncertainty around an estimate, commonly expressed as a half-width for an interval. It communicates how precisely a survey estimates a population quantity.
Population mean: The arithmetic average of all values in a defined population. It is a common parameter describing a population's central value.
Sampling distribution: The probability distribution of a statistic across repeated samples drawn under the same conditions. It describes how estimates of a fixed parameter vary from sample to sample.

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