The probability model is a technique wherein samples are gathered in a way that gives all the individuals in the population an equal chance of being selected.Many consider this to be the more methodologically rigorous approach to sampling because it eliminates social biases that could shape the research sample.
The non-probability model is a technique in which samples are gathered in a way that does not give all individuals in a population equal chances of being selected.
While choosing a non-probability method could result in biased data or a limited ability to make general inferences based on the findings, there are also many situations in which choosing this kind of sampling technique is the best choice for the particular research question or the stage of research.
Ultimately, though, the sampling technique you choose should be the one that best allows you to respond to your particular research question.
There are four kinds of probability sampling techniques.
This is technically called a systematic sample with a random start.
A stratified sample is a sampling technique in which the researcher divides the entire target population into different subgroups or strata, and then randomly selects the final subjects proportionally from the different strata.
Since it's rarely possible to study an entire population of focus, researchers use samples when they seek to collect data and answer research questions.
A sample is simply a subset of the population being studied; it represents the larger population and is used to draw inferences about that population.
This technique is useful when studying a sensitive topic that people might not openly talk about, or if talking about the issues under investigation could jeopardize their safety.
A recommendation from a friend or acquaintance that the researcher can be trusted works to grow the sample size.