Designing Studies

Population, census, and sample

The population in a statistical study is the entire group of individuals we want information from.

A Census collects data from every individual in the population.

A sample is a subset of individuals in the population from which we collect data.

Convenience Sample

Choosing individuals from the population who are easy to reach results in a convenience sample

Bias

The design of a statistical study shows bias if it is very likely to underestimate or very likely to overestimate the value you want to know

Voluntary Response Sample

Consists of people who choose themselves by responding to a general invitation

Random Sampling

Involves using a chance process to determine which members of a population are included in the sample

Simple Random Sample (SRS)

A simple random sample (SRS) of size n is chosen in such a way that every group of n individuals in the population has an equal chance to be selected as the sample

Stratified Random Sample and Strata

Split population into homogeneous (similar) groups (called strata) based on anticipated response, select an SRS from each stratum, and combine the SRSs to form the overall sample

Cluster sample and clusters

Split the population into groups (often based on location) called clusters, randomly select clusters, and include each member of the selected clusters in the sample

Undercoverage

Occurs when some members of the population cannot be chosen in a sample

Nonresponse

Occurs when an individual chosen for the sample can’t be contacted or refuses to participate