SAMPLING

Sampling is a crucial aspect of research that enables researchers to collect data about a population of interest. The primary objective of sampling is to acquire data representative of the entire population, which can be challenging due to the population's size and diversity. To achieve a representative sample, researchers must ensure that the sample consists of individuals with the same characteristics as the population of interest. This can be achieved through various sampling techniques, such as random, purposive, and quota.

A representative sample consists of individuals with the same characteristics as the population. For example, suppose a researcher knows that 55% of the population he intends to study is male, 18% are African-American, 7% are homeless, and 23% earn more than 100,000 euros. In that case, he/she should try to match these characteristics in the sample to represent the population.

Random sampling is used when researchers cannot match the population's characteristics in the sample. Randomization helps to offset confounding effects by randomly selecting cases. Fig. 8. displays a graphical representation of a population (people, events, households, institutions, or something else) that is the subject of research, a sample frame (set of units from which a sample will be drawn: in the case of a simple random sample, all units in the sampling frame have an equal chance of being drawn and of occurring in the sample), and a sample (the subset of the population chosen for the research or survey).

A biased sample is neither representative nor random. Its answers do not reflect those obtained from the entire population. Survey responses can suffer from different biases, such as selection bias, non-response bias, and response bias. Sampling error is always present due to statistical imprecision.

Convenience sampling is a non-probabilistic sampling technique where people are chosen because they are readily available. In purposive sampling, subjects are selected based on predetermined characteristics. Volunteer and snowball sampling are other non-probabilistic sampling techniques employed in populations that are difficult to access. Quota sampling is a technique used in online surveys where sampling is done based on pre-established criteria. For instance, many polls have an implicit quota, such as customer satisfaction.