Sampling Distributions

These flashcards cover key vocabulary terms and concepts related to sampling distributions as taught in IST 292 Statistics.

Sampling Distribution

The probability distribution of a statistic calculated from a sample.

Parameter

A numerical descriptive measure of a population.

Sample Statistic

A numerical descriptive measure of a sample, calculated from observations in that sample.

Point Estimator

A rule or formula that provides a single number as an estimate of a population parameter.

Standard Error

The standard deviation of the sampling distribution of a statistic.

Unbiased Estimator

An estimator whose expected value equals the true value of the parameter being estimated.

Degrees of Freedom

The number of independent values that can vary in an analysis; typically the sample size minus the number of parameters estimated.

t Distribution

A probability distribution used for small sample data; resembles a normal distribution but is generally wider and shorter.

Chi-Square Distribution

A distribution that describes the distribution of a sum of squared standard normal variables.

F Distribution

A probability distribution that arises frequently in the context of variance analysis.

Error of Estimation

The difference between the estimate provided by a sample statistic and the true population parameter.

Normal Distribution

A probability distribution that is symmetric about the mean, indicating that data near the mean are more frequent in occurrence than data far from the mean.

Bernoulli Distribution

A discrete distribution representing the outcomes of a single trial that can come out as a success or failure.

Binomial Distribution

The distribution of the number of successes in a fixed number of independent Bernoulli trials.

Standard Deviation

A measure of the amount of variation or dispersion of a set of values.