Statistics - Sampling methods


Sampling methods are the ways to choose people from the population to be considered in a sample survey. Samples can be divided based on following criteria.

  • Probability samples - In such samples, each population element has a known probability or chance of being chosen for the sample.

  • Non-probability samples - In such samples, one can not be assured of having known probility of each population element.

Probability sampling methods

Probability sampling methods ensures that the sample choosen represent the population correctly and the survey conducted will be statistically valid. Following are the types of probability sampling methods:

  • Simple random sampling. - This method refers to a method having following properties:

    • The population have N objects.

    • The sample have n objects.

    • All possible samples of n objects have equal probability of occurence.

    One example of simple random sampling is lottery method. Assign each population element a unique number and place the numbers in bowl.Mix the numbers throughly. A blind-folded researcher is to select n numbers. Include those population element in the sample whose number has been selected.

  • Stratified sampling - In this type of sampling method, population is divided into groups called strata based on certain common characteristic like geography. Then samples are selected from each group using simple random sampling method and then survey is conducted on people of those samples.

  • Cluster sampling - In this type of sampling method, each population member is assigned to a unique group called cluster. A sample cluster is selected using simple random sampling method and then survey is conducted on people of that sample cluster.

  • Multistage sampling - In such case, combination of different sampling methods at different stages. For example, at first stage, cluster sampling can be used to choose clusters from population and then sample random sampling can be used to choose elements from each cluster for the final sample.

  • Systematic random sampling - In this type of sampling method, a list of every member of population is created and then first sample element is randomly selected from first k elements. Thereafter, every kth element is selected from the list.

Non-probability sampling methods

Non-probability sampling methods are convenient and cost-savvy. But they do not allow to estimate the extent to which sample statistics are likely to vary from population parameters. Whereas probability sampling methods allows that kind of analysis. Following are the types of non-probability sampling methods:

  • Voluntary sample - In such sampling methods, interested people are asked to get involved in a voluntary survey. A good example of voluntary sample in on-line poll of a news show where viewers are asked to participate. In voluntary sample, viewers choose the sample, not the one who conducts survey.

  • Convenience sample - In such sampling methods, surveyor picks people who are easily available to give their inputs. For example, a surveyer chooses a cinema hall to survey movie viewers. If the cinema hall was selected on the basis that it was easier to reach then it is a convenience sampling method.