Types of sampling

What are 2 categories of sampling?

1. Non-probability sampling

2. Probability sampling

Non-probability sampling

• Convenience sampling

• Volunteer sampling

• Quota sampling

Convenience sampling

Selecting members of the population that are easily accessible

e.g. immediate family members & friends

Volunteer sampling

Selecting members of the population willing to participate in the investigation

e.g. open access online questionarie

Quota sampling

Decide on a quota of units to be sampled for each subgroup of the population in order to obtain a more representative sample

E.g. interviewing at least 5 people for each age group (students, working adults & elderly)

Advantages of quota sampling

Reach out to more groups of the population

Disadvantages of quota sampling

May be susceptible to skewed results as units are sampled subjectively by the researcher since the research deliberately sets the proportions of strata (subpopulation within a population)

Probability sampling

• Simple random sampling

• Systematic random sampling

• Proportionate stratified sampling

Simple random sampling

Giving each member of the population an equal chance of being selected for the investigation

e.g. rolling a die and selecting from a list of possible questionnaire respondents

Advantages of simple random sampling

Cheaper, fairer & easy to administer

Disadvantages of simple random sampling

Skewed sample

May result in higher costs

Systematic random sampling

Selecting every nth element of the sampling frame, beginning with a randomly chosen point.

e.g. roll a dice to determine sampling intervals, if value is 5, then every 5th person will be chosen from a list of respondents to interview.

Advantages of systemic random sampling

Better representation of the population compared to simple random sampling

Disadvantages of systematic random sampling

Run the risk of sampling a part of the population that may share overlapping characteristics.

e.g. sampling people from the same SES background

Proportionate stratified

1. Sample size is first determined

2. (strata) Sample size of each subgroup is determined in proportion to the proportion of the subgroup against the actual population size.

E.g. If the sample size is 100, and the elderly make up 10% of the total population, sample size of the elderly would be 10

Advantages of proportionate stratified sampling

Better coverage and representation of the population as a whole

Disadvantages of proportionate stratified sampling

• Some stratas might be difficult to define (age group ethnicity)

• Census data (official collection of demographic, social & economic infog of a regional/national population) might not be available.