Sampling methods

what is a population?

all individuals who share a particular characteristic a researcher is interested in

what is a sample?

group of people who take part in an experiment, drawn from target population and is assumed to be representative of that whole population

what is the target population?

specific subset of the population that the researcher wants to study

what is generalisation?

The extent to which the findings and conclusions from a study can be applied to the population

what are the different types of sampling methods?

Opportunity, random, stratified, systematic, volunteer

What is random sampling?

where every individual in the target population has an equal chance of being selected to participate in the study

strength of random sampling- bias

minimises selection bias as each member has an equal chance of being selected- sample more likely to reflect diversity of population, enhancing generalisability of results-more confident findings apply beyond sample

strength of random sampling- researcher influence

reduces researcher influence (random selection process), so researchers personal beliefs/expectations less likely to affect results- maintains objectivity and scientific integrity

weakness of random sampling- time

impractical and time-consuming- difficult tp create complete list of large populations

weakness of random sampling- unrepresentative

unrepresentative by chance- method doesn't guarantee perfectly balanced sample every time

what is systematic sampling?

every nth person of target population selected

strength of systematic sampling- efficiency

simple and efficient- useful for large populations so more practical for real-world contexts

strength of systematic sampling- researcher bias

reduces researcher bias- selection follows a predetermined system, maintaining objectivity, increases finding's reliability

weakness of systematic sampling-patterns

may be an underlying pattern in population list so sample becomes biased (periodicity)

weakness of systematic sampling- list

can be time consuming to create a complete and ordered list, if incomplete or not randomised sample may not accurately reflect target population- reduces generalisability

what is opportunity sampling?

participants selected based on their availability and willingness to take part at the time of the study

strength of opportunity sampling- speed

quick to conduct, needs minimal planning good for when time/funding is limited- speed and practicality

strength of opportunity sampling

cost effective- no need for expensive recruitment campaigns so suitable for small-scale studies

Weakness of opportunity sampling- researcher bias

may choose participants who they believe will give desired responses- skews results

weakness of opportunity sampling-bias

high risk of bias- no random selection so sample may not be representative, reducing generalisablity of findings

what is volunteer sampling

Involves participants selecting themselves to be part of the sample

strengths of volunteer sampling

cost effective and quick as participants come forwards themselves- suitable for small scale/pilot studies. Volunteers usually more engages and cooperative- higher quality data

weakness of volunteer sampling

volunteer bias- attract a narrow demographic- skewed results, not representative of wider population

What is stratified sampling?

Dividing the population into subgroups (strata) then selecting a sample from each of these groups

how to conduct stratified sampling?

define target population, identify strata which make up population, determine proportion needed for sample from stratum, select participants needed to make up proportion for that strata selected via random sampling

strength of stratified sampling- representativeness

reduced risk of some groups being underrepresented, enhancing generalisability of findings to wider population

strength of stratified sampling- analysis

allows for meaningful subgroup analysis as each stratum deliberately sampled

weakness of stratified sampling-time

time consuming and complex to organise- difficult for large and diverse populations

weakness of stratified sampling- misclassification

if placed into wrong strata sample may become biased