Sampling

3.2.3 Research Methods

sampling

selecting a subset of individuals from the larger population, to study and draw inferences about the entire population

sampling technique

method used to select people from the population

bias (sampling)

occurs when a certain group is under- or overrepresented within the sample group

generalisation

the extent to which findings from an investigation can be applied to the wider population

population

a group of people who are the focus of the researcher’s work, from which a smaller sample is selected

random sampling

every member of the population has the same chance of being chosen (e.g. assigning each participant a number then using a random number generator)

systematic sampling

selecting every n^th member of the population (e.g. every 5^th person on a register)

opportunity sampling

researcher selects anyone who is willing and available (e.g. waiting on a street)

volunteer sampling

participants choose to take part themselves (e.g. answering a postal questionnaire)

stratified sampling

researcher divides the population into subgroups based on key characteristics and randomly selects participants from each subgroup proportionally

strengths of random sampling

free from researcher bias

weaknesses of random sampling

• difficult and time consuming

• sample may not represent population

strengths of systematic sampling

• free from researcher bias

• fairly representative

weaknesses of systematic sampling

labour intensive

strengths of stratified sampling

guaranteed to obtain a representative sample » findings are generalisable

weaknesses of stratified sampling

• very labour intensive

• some strata may be overrepresented in a diverse population

strengths of opportunity sampling

easy to obtain

weaknesses of opportunity sampling

• lacks population validity

• high level of researcher bias

strengths of volunteer sampling

easy to obtain

weaknesses of volunteer sampling

• volunteer bias

• lacks population validity