sampling techniques

A researcher obtains their sample from the target population.

The researcher draws the sample from the target population and then generalises the findings across the target population.

False. Stratified sampling is the least biased of all the sampling methods.

b. Using whoever is present at the time of sampling is not how a random sample is obtained.

False. Random sampling can be time-consuming and impractical. It is not always possible to get access to all the information on a target population, and not everyone selected may want to participate.

a. A strength of random sampling is that it eliminates the chance of researcher bias. This is because the researcher has no control over who is selected to be in the sample.

Systematic sampling involves selecting every nth person from a list to make a sample. E.g., the researcher selects, for example, every 10th or 100th or 1000th person on a database.

The sampling interval is calculated by dividing the population size by the required sample size. E.g.,From a population of 100,000, a sample of 2500 is required so 100,000 divided by 2500 = 40; thus, every 40th person on the population list is selected for the sample.

True. Systematic sampling is a quick, easy and cost-effective sampling method compared to random sampling. This makes it popular amongst researchers and likely to be agreed upon by funding bodies.

b. Systematic sampling is not completely free from bias as the selection process can interact with a hidden periodic trait. A periodic trait occurs when every nth person in the sample has the same or similar characteristics. E.g., If every 10th person on the list is a 19-year-old female nurse, then this would constitute the sole demographic in the sample.

Stratified sampling generates a small-scale reproduction of the target population, i.e., the sample within each category (e.g., % of males/females) is proportional to the overall population total.

A stratified sample is representative of the target population, making it easy to generalise from.

False. Stratified sampling can be difficult and time-consuming. It is not always possible to get access to all the information on a target population.

Opportunity sampling involves the researcher obtaining their sample from those who are present and available at the time and who are willing to take part in the research.

c. Opportunity sampling is also known as convenience sampling.

b. The main strength of opportunity sampling is that is quick and easy.

False. It is not possible to generalise from an opportunity sample as the sample only represents those who were available and willing to participate at the time.

a. Volunteer sampling is also known as self-selecting sampling.

To obtain a volunteer sample a researcher must advertise for participants.

c. Participants in a **volunteer sample are likely to be willing and enthusiastic about the research. They have made a **conscious decision to take part in the research which means that they are less likely to jeopardise the study and its results.

a. A limitation of using volunteer sampling is that it can result in volunteer bias. The results are not easy to generalise as volunteer participants often have personality traits in common e.g. sociable, outgoing etc.