Probability vs. Non-Probability Sampling Methods in Research
Probability Sampling
In probability sampling, a random sample is used, where each basic element has a known probability of being selected in the sample.
Characteristics:
- Each element is randomly selected and has the same probability of selection.
- Error and confidence can be calculated.
- Results can be generalized.
- It is the only method that can evaluate the representativeness of the sample.
- It is more expensive than non-probability sampling.
- It is slower and more complicated.
Types of Probability Sampling:
Simple Random Sampling
All elements of the population have the same probability of selection.
Selection: List all units of the population, then choose the sample randomly.
Utilization: Recommended for small-scale surveys (e.g., audience ratings, telephone surveys).
Systematic Random Sampling
Select a single element at random from the population, and the rest are determined by the first.
Selection: Ordered units of sampling are calculated, the selection interval K (N/n) is calculated, a number between 1 and K is chosen as the starting point, and the elements will be a, a+1.
Utilization: Commercial investigations with an orderly and large population size (N), easier fieldwork.
Stratified Random Sampling
A stratified sample is obtained by starting with a series of random samples selected from groups that make up a population. These groups are called strata. Strata are formed by different behaviors.
Selection: The population is divided into K groups (exclusive strata). A simple random sample is selected from each stratum. The total sample size (n) is distributed among the different strata. Proportional allocation: ni = Ni/N, i = 1…k.
Characteristics:
- Should be used when each layer is homogeneous.
- Yields more accurate estimates.
- The population is treated differently in each stratum.
- The biggest drawback is the design.
- Stratification variables are related to the study.
- This sampling is very common in market research.
Non-Probability Sampling
In non-probability sampling, the sample units are not selected at random but are chosen by individuals.
Characteristics:
- The selection of the sample is not random.
- It is not based on any theory of probability.
- The cost and difficulty of design are more limited.
- It is not possible to calculate errors and the confidence of the estimates.
Types of Non-Probability Sampling:
Convenience Sampling
The sample is selected according to the researcher’s convenience and ease of availability.
Judgment Sampling
The choice of the sampling unit is made by an expert. Their view predominates on the units that can represent the investigation.
Quota Sampling
Uses an empirical method. The researcher aims to obtain a sample that is similar to the population in some characteristics.
Characteristics:
- Identify groups that meet certain conditions (age, sex, habitat).
- Determine the sample size in each group.
- It differs from stratified sampling in that people are selected, and quotas may be marginal or crossed.
Snowball Sampling
Each interviewed sampling unit is located by another person. Used for specialized studies.
Route Sampling
The interviewer is given specific rules on the route or path to be followed in choosing the sample.
Other Sampling Methods
Cluster Sampling
The sampling unit is not an element of the population but a set of them, called a cluster. There is strong heterogeneity among its elements and homogeneity among clusters. Usually applied in surveys conducted in cities where a cluster can be defined as a block of homes, reducing the cost of the survey. It is appropriate for clusters with few elements. Usually applied in combination with other sampling methods.
Multistage Sampling
It is a refinement of cluster sampling. 1 cluster, 2 samples.
Characteristics:
- Less efficient than simple random sampling.
- Increases errors.
- Shares sample size at different stages.