5.3 Sampling Techniques

Population – all individuals who belong in the context being examined. (think universal set)

Sample – a group within the population that is representative of the whole.

Ex 1 Identify the Population for the following survey questions

(a) Whom do you plan to vote for in the next Ontario election?

(b) What is your favourite type of baseball glove?

(c) Do women prefer to wear ordinary glasses or contact lenses?

Sampling Methods

Simple Sample – assign a random number to every possible member of population, select those who satisfy the condition of your sample (e.g. assign a 0 or 1 to every member of population, select the 1s for your sample)

Systematic Sample – go through the population sequetially and select members of the sample at regular intervals. (e.g. select every 4th member of the population for your sample.)

Stratified Sample – when your population has smaller groups that share certain characteristics, take a sample from each strata relative to the size of the strata within the population

Cluster Sample – sampling 'chunks' of a population assuming that the 'chunks' are representative of the population.

Multi-Stage Sample – Organizing your population into various layers and then randomly selecting different layers at different stages.

Voluntary-Response Sample – The researcher invites whomever would like to participate in the survey to complete the survey.

Convenience Sample – selecting members of your sample where they are found quite easily.

Remember:

• A carefully selected sample can provide accurate information about a population.

• Selecting an appropriate sampling technique is important to ensure that the sample reflects the characteristics of the population. Randomly selected samples have a good chance of being representative of the population.

• The choice of sampling technique will depend on a number of factors, such as the nature of the population, cost, convenience, and reliability.

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