Sampling Methods | Sociology for GCSE/IGCSE - Year 11 PDF Download

Sampling

Sampling is a critical part of the research process where sociologists identify the population they wish to study, such as:

• Individuals (e.g., students, stay-at-home dads, single mothers)
• Institutions (e.g., schools, hospitals, prisons)

Studying an entire population is often impractical, so researchers select a sample, or a subgroup, from the population to study.

The sample is typically drawn from a sampling frame, which is a complete list of all members of the population under study, for example:

• School registers
• Voters’ roll
• Royal Mail’s list of postcodes

If the sampling frame is inaccurate, the resulting sample may not be representative of the broader population, making it challenging to generalize findings to the wider group.

Sampling Methods

Sociologists use various sampling techniques, categorized as probability and non-probability sampling.

Probability Sampling

In probability sampling, every member of the sampling frame has a known chance of being selected.

Sampling Techniques:

• Random Sampling
  Every individual in the population has an equal chance of being chosen. Researchers may use random name generators to select participants.
• Systematic Random Sampling
  Involves selecting every 'nth' member from the sampling frame (e.g., every 5th name on a list). For instance, if a population has 500 students and a sample of 100 is needed, a researcher randomly picks a number between 1 and 5 and continues selecting every 5th name until the sample size is reached.
• Stratified Random Sampling
  The population is divided into subgroups (strata) based on characteristics like age or gender (e.g., females 30 and under, males 31 and over). A random sample is then drawn from each stratum proportional to its size in the population. For example, if 20% of the population is females aged 31+, the sample must include 20% females aged 31+.

Evaluation of Probability Sampling

Strengths:

• Minimizes bias since the researcher has no influence over participant selection.
• Aims to produce a representative sample of the population.

Weaknesses:

• More time-consuming and challenging than non-probability methods, as obtaining an accurate sampling frame can be difficult.
• Selected participants may decline to participate, preventing a fully representative sample.

Non-Probability Sampling

Non-probability sampling is used when a sampling frame is unavailable, such as for populations like homeless individuals or class A drug users.

Sampling Techniques:

• Snowball Sampling
  The researcher starts with one member of the population, builds trust, and relies on them to identify others who may participate in the study.
• Quota Sampling
  Commonly used in market research, this involves interviewing a specific number (quota) of people from predefined categories, proportional to their representation in the population (similar to stratified sampling).
• Purposive Sampling
  Participants are chosen based on specific characteristics, such as being a headteacher, an MP, or a cancer survivor.

Evaluation of Non-Probability Sampling

Strengths:

• Convenient and less time-consuming than probability sampling.
• Often the only feasible method for accessing certain populations.

Weaknesses:

• Prone to bias, as the researcher influences participant selection (e.g., avoiding individuals they dislike).
• Non-representative samples limit the ability to generalize findings to the broader population.