Statistics LT 5B

Population Parameter

A value that describes a characteristics of a population or model

Sample Statistic

A value that describes a characteristic of a sample

Sampling Variability

the idea that the value of a statistic will vary from one sample to the next

Sampling distribution of a statistic

the distribution of values taken by the statistic in all possible samples
of the same size from the same population; Sampling distributions may be approximated by:


1. repeated computer simulations or hands-on simulations
2. a theoretical sampling distribution derived from the rules of probability

Unbiased estimator

A statistic which has a sampling distribution equal to the value of the parameter being estimated

Random Sampling Methods

produce unbiased estimators.

When using an unbiased estimator, we’re equally likely to get a sample that overestimates the parameter as one that underestimates the parameter.

Variability of a statistic

the spread of its
sampling distribution. (precision)

* Larger random samples have less variability than smaller random samples.
* Larger random samples have the same amount of bias as smaller random samples.

The best sampling methods have low bias and low variability.