Sampling

• A target population is the wider group that the researchers draws the sample from and who they want to generalise the findings to.
• A target population can be a large group/ cohort or wider community or culture.
• A target population is an entire group with specified characteristics.
• The different types of sampling methods are random sampling, stratified sampling, systematic sampling, opportunity sampling and volunteer (self-selected) sampling.
• A target population refers to the entire group of individuals that a researcher wants to study, while a sample refers to the specific group of individuals that are selected to participate in the study.
• A target population is usually too large to study in its entirety, so sampling methods are used to select smaller samples in which to study.
• An unrepresentative sample is one that does not reflect the distribution of characteristics of the target group, so cannot be generalised to the target population, and is therefore biased.
• A representative sample is a smaller group selected from the target population who have similar characteristics, which would allow us to generalise.
• Having a representative sample increases the generalisability of the results.
• Having a unrepresentative sample adds bias to the findings and limits the ability to generalise.
• Random sampling gives every member of the target group an equal chance of being selected for the sample (e.g. by assigning a number to each member or by using a random number generator).
• Random sampling is a good technique as it gives everyone a fair chance of being selected, however this can still be biased.
• Random sampling can be biased, as participants with similar characteristics can still be selected.
• Random sampling ensures that every member of the target group has an equal chance of being selected by using a random selection process where each member has an equal probability of being chosen.
• Random sampling is a method of selecting a sample from a population in which each individual has an equal chance of being chosen, ensuring that the sample is representative of the population.
• Random sampling can be time consuming.
• It can be impractical/ impossible to use a completely random technique, as the target group may be too large to assign numbers to.
• A systematic method for selecting participants from a target population uses a set system. For example, choosing every 5th person in a list.
• A systematic sampling technique does not give everyone an equal chance of being selected, as participants are usually placed in order.
• One way to reduce bias in a systematic sampling method is to use a list that has been randomised, giving people a fair chance of being selected.
• If every 5th person in the list was male, you would have only males in your sample. This would not be representative.
• A stratified sample should contain participants with similar key characteristics or demographics in exact proportion to the target population.
• A stratified sample must represent the target population in exact proportion. If the population was 70% male, 30% female, your sample must be the same.
• Stratified sampling takes more time and resources to plan.
• In a stratified sample, care must be taken to ensure each key characteristic present in the population is selected across strata, otherwise this will result in a biased sample.
• In opportunity sampling participants are selected by whoever is accessible and willing to take part at the time.
• An opportunity sample takes participants by chance who are available at the time.
• An opportunity sample is more likely to be biased as participants are selected by the researcher themselves.
• Opportunity sampling is easy and inexpensive to carry out.
• Opportunity samples may not be representative which could lead to bias. All females could be selected, as they are the only ones available at the time.
• Random sampling involves selecting a sample from a population in a way that everyone has an equal chance of being chosen, while opportunity sampling involves selecting participants who are readily available and easily accessible.
• Opportunity sampling allows for quick and convenient data collection, as participants are selected based on their availability and accessibility.
• A volunteer sample consists of people who have self-selected themselves to be in the study.
• Volunteer samples are sometimes called self-selected samples.
• Volunteer samples often gain large sample sizes through reaching a wide audience, for example with online advertisements.
• In volunteer sampling those who respond may all display similar characteristics, which is not representative.
• Some advantages of using volunteer samples in research include convenience, cost-effectiveness, and the potential for high levels of participant engagement and motivation.
• Volunteer sampling allows for easy recruitment of participants and can be cost-effective.
• A potential drawback of using volunteer samples in research is that they may not be representative of the larger population, leading to biased results.
• Volunteer samples are at higher risk of demand characteristics, as they are more motivated and willing.