4.1 Samples and Surveys

Population

The entire group of individuals

Census

Data from all of the population

Sample

A subset of the population

Convenience sample

Easy-to-reach sample (first 100 people that walk into a store, your entire first period class)

Voluntary response sample

Open invitation to join the sample (a mail-in survey sent to everyone in the district for people to choose whether they want to complete the form or not)

Random sample

Chance process to select random individuals

Simple random sample

The simplest method to choosing a random sample

Stratified random sample

More complex method of random sampling where a population is divided into similar groups (called strata), and a select few from each group is chosen. This guarantees some level of representation which helps to bring more accurate data.

Cluster sample

Sampling based on location, into groups of clusters.

Systematic random sample

More methodic method of random sampling, where every nth member is chosen

Inference

Conclusions drawn from samples

Margin of error

Binds likely errors

Undercoverage

Some of the population isn’t represented or cannot be chosen (sampling error). For example, older people are less likely to have mobile phones, so a survey carried out by calling mobile phone numbers will not properly represent the older generation.

Nonresponse

Some of the samples do not participate. If the sample is ALREADY chosen, and people ACTIVELY choose not to send in their response.

Voluntary response bias

People can CHOOSE to be part of the sample. This makes the data collected more extreme, as people with more middle-ground views will not feel strongly and take the time to respond.

Response bias

Systematic pattern of incorrect responses. (People will say to a survey they do not do drugs in fear of