Statistical Sampling Methods

Random Sampling

A procedure where every possible sample has an equal chance of being selected

Positives of Random Sampling

Produces an unbiased sample

Negatives of Random Sampling

Hard to practice

Needs a list of the entire population and everybody to respond

Time consuming and expensive

Opportunity Sampling

Involves choosing respondents based upon their availability and convenience

Positives of Opportunity Sampling

Cheap and convenient

Only sampling from those who are available and willing to take part

Negatives of Opportunity Sampling

Does not produce a simple random sample

May introduce bias and not be generalisable

Systematic Sampling

Taking participants at regular intervals from a list of the population, with the starting point chosen at random

Positives of Systematic Sampling

Avoids unwanted clustering of data

Practically easier then using random number generators

Negatives of Systematic Sampling

Needs a list of the entire population

Less random than simple random as no longer independent

Stratified sampling

Splitting the population into groups based on factors relevant to the research, then random sampling from each group in proportion to the size of that group

Positives of Stratified Sampling

Produces a sample representative over the factors identified

Random method

Negatives of Stratified Sampling

Needs a list of the entire population with additional information about each member

Time consuming and expensive

Determining which factors to consider is not always obvious

Quota Sampling

Splitting the population into groups based on factors relevant to the research, then opportunity sampling from each group until a required number of participants are found

Positives of Quota Sampling

Ensures the sample is representative over the factors identified

Negatives of Quota Sampling

May introduce bias and not be generalisable

Cluster Sampling

Splitting the population into clusters based on convenience and then random choosing some clusters to study further

Positives of Cluster Sampling

Cheaper and easier than other random methods

Negatives of Cluster Sampling

Less accurate than other random methods - clusters may not be representative