Kaarten: Methodology - Chapter 5 - Selecting Research Participants | Quizlet

Sample

A set of individuals selected form a population and usually is intended to represent the population in a research study.

Population

The entire set of individuals of interest to a researcher. Although they usually do not participate all in a research study, the results from that study are generalized to them.

Target population

The group defined by the researcher's specific interests. E.g.: children of divorced parents, elementary-school-aged children

Accessible population

Those people that can be recruited as a sample of the target population.

Representativeness

The extent to which the characteristics of the sample accurately reflect the characteristics of the population.

A representative sample

A sample with the same characteristics as the population

A biased sample

A sample with different characteristics from those of the population.

Selection bias or sampling bias

Occurs when participants or subjects are selected in a manner that increases the probability of obtaining a biased sample.

The law of large numbers

A large sample is probably more representative than a small sample. Or the larger the sample size, the more likely it is that values obtained from the sample are similar to the actual values for the population.

sampling

The process of selecting individuals to participate in a research study.

Sampling methods / techniques / procedures

Basically exists out of two categories: probability sampling and non-probability sampling.

Probability sampling

When the entire population is known and each individual in the population has a specifiable probability of selections, and sampling occurs by a random process based on the probabilities.

Random process

A procedure that produces one outcome form a set of possible outcomes. The outcome must be unpredictable each time, and the process must guarantee that each of the possible outcomes is equally likely to occur.

Non-probability sampling

When the population is not completely known, individual probabilities cannot be known, and the sampling method is based on factors such as common sense or ease, with an effort to maintain representativeness and avoid bias.

Simple random sampling

When each individual in the population has an equal chance of being selected.

Independent selections

When the probabilities of selecting any particular individual stays constant

Systematic sampling

A type of probability sampling that is very similar to simple random sampling: after listing all the individuals in the population, then obtaining a sample by selecting every nth name. N is calculated by dividing the population size by the desired sample size.

Stratified random sampling

When you start with identifying the specific subgroups to be included in the sample, then select equalised random samples from each as in simple random sampling and then finally combine the subgroup samples into one overall sample.

Layers / subgroups

Strata

Proportionate (stratified) random sampling

When researchers try to improve the correspondence between a sample and a population by deliberately ensuring that the composition of the sample matches the composition of the population. Commonly used for political polls. The procedure is almost the same as the stratified random sampling but with the goal of obtaining the correspondence between a sample and a population, where in genuine stratified random sampling it can be any equalised samples.

Cluster sampling

This sample selection procedure can be used when well-defined clusters exists by selecting these or a number of these clusters to become the desired number of individuals in the sample. It is relatively quick and the measurement of individuals can often be done in groups. e.g.: a class of students.

Convenience / opportunity / accidental / haphazard - sampling

When researchers simply use as participants those individuals who are easy to get. It is considered as a weak form of sampling because there is a strong possibility that the obtained sample is biased.

Quota sampling

A method for controlling the composition of a convenience sample ensuring that subgroups are equally represented in a convenience sample. But there is a high probability of a biased sample.