ST 311 Statistics Notes/Vocab

Quantitative

Numbers

Categorical

No numbers; descriptive

Bias

Samples that are more likely to produce some outcomes than others. The resulting statistics may be too high or low.

Convenience Sample

Samples that are easy to collect. Often have bias or poor representation of the population.

Volunteer Response Sample

Samples that are self-selected based on a group(s) that respond to a general appeal.

Simple Random Sample (SRS)

A sample of (n) subjects is selected in a way that every possible sample of the same size (n) has the same chance (or probability) of being chosen.

Stratified Sample (Group from group)

Subdivide the population into 2 subgroups (strata) so that the subjects within the same subgroup share the same characteristics. The draw a sample from each subgroup. The number sampled from each stratum may be done proportionally with respect to the size of the population.

Cluster Sample (Everyone)

Divide the population area into naturally occurring sections (clusters) then randomly select some of those clusters and choose all the members from those selected clusters.

Systematic Sample

Select some starting point and the select every Xth element in the population. This works well when units are in some order. (Assembly lines, houses on a block, people in a line)

Multistage Sample

Collect data with some combination of of the basic sampling methods.

Population

Complete collection of all measurements or data that are being considered

Sample

Subsect of members selected from a population (Good sample = random and representative)

Parameters

A numerical measurement describing some characteristics of a sample

Discrete Data

Result when the data values are quantitative and the number of values is finite or countable (whole numbers)

Continuous Data

Result from infinitely many possible quantitative values, where the collection of values is not countable (Can contain decimals)