Sampling Methods and Population Parameters

A collection of vocabulary flashcards based on key concepts related to sampling methods, population parameters, and statistical errors discussed in the lecture.

Margin of Error

The range within which the true population parameter is expected to fall, calculated as $\frac{1}{ ext{sqrt}(n)}$ where n is the sample size.

Simple Random Sample

A probability-based sampling method where every unit in the sampling frame has an equal chance of being selected.

Population Parameter

A value that summarizes a characteristic of the entire population.

Stratified Random Sample

A sampling method that divides the population into subgroups (strata) and takes a random sample from each.

Cluster Sampling

A sampling technique where the population is divided into clusters, and entire clusters are randomly selected.

Systematic Sampling

A method that selects every nth member of the population list after randomly choosing a starting point.

Census

A complete enumeration of the entire population which allows for the exact determination of population parameters.

Sampling Frame

A list or database from which a sample is drawn, containing all units of the population.

Probability-based Sampling Methods

Sampling methods that use random selection, ensuring that every individual has a known chance of selection.

Non-Sampling Error

Errors that occur due to factors other than the sampling process, such as flaws in survey design.

Sampling Error

The error that arises from taking a sample instead of a full census, which can lead to inaccuracies in estimating population parameters.

Coverage Error

A type of non-sampling error that occurs when the sampling frame does not include the entire population.