Chapter 7: Sampling and Sampling Distributions

These flashcards cover key concepts related to sampling and sampling distributions, including definitions, types of sampling methods, and important statistical terms.

Element

The entity on which data are collected.

Population

A collection of all the elements of interest.

Sample

A subset of the population.

Sampled Population

The population from which the sample is drawn.

Frame

A list of the elements that the sample will be selected from.

Point Estimation

A form of statistical inference that uses sample data to compute a value that estimates a population parameter.

Simple Random Sample

A sample selected such that each possible sample of a given size has the same probability of being selected.

Sampling Error

The difference between the value of the sample statistic and the corresponding value of the population parameter.

Standard Error of the Mean

The standard deviation of the sampling distribution of the sample mean.

Central Limit Theorem

The theorem stating that the sampling distribution of the sample mean will be approximately normal if the sample size is sufficiently large.

Expected Value

The mean of a probability distribution, which, for a point estimator, is equal to the population parameter.

Finite Population Correction Factor

A factor used when sampling without replacement from a finite population.

Sampling Distribution of the Sample Proportion

The probability distribution of all possible values of the sample proportion.