Consecutive Sampling

Consecutive Sampling: Definition

Consecutive sampling is defined as a non-probability sampling technique where samples are picked at the ease of a researcher more like convenience sampling, only with a slight variation. Here, the researcher picks a sample or group of people and conduct research over a period of time, collect results, and then moves on to another sample.

This sampling technique gives the researcher a chance to work with multiple samples to fine tune his/her research work to collect vital research insights.

In most of the sampling techniques in research, a researcher will finally infer the research, by coming to a conclusion that experiment and the data analysis will either come down to accepting the null hypothesis or disapproving it and accepting the alternative hypothesis.

Null hypothesis is defined as a statistical hypothesis in which no significant difference exists between the set of variables involved in the research or experiment. In the statistical terms, the original or default statement is often represented by H0. If null hypothesis is accepted then a researcher will not make any changes in opinions or actions. Null hypothesis is indirect or implicit.

An alternative hypothesis is the opposite of null hypothesis. In this statistical hypothesis, there is a relationship between the two variables involved in the study or research. An alternative hypothesis is accepted when a null hypothesis is rejected. In alternative hypothesis the testing is direct and explicit. An alternative hypothesis is denoted by H1.  

However, in consecutive sampling, there is a third option available. Here, a  researcher can accept the null hypothesis, if not the null hypothesis, then its alternative hypothesis and if neither of them is applicable then a researcher can select another pool of samples and conduct the research or the experiment once again before finally making a research decision.

Learn more: Non-Probability Sampling for Social Research

Consecutive Sampling Example

  • One of the most common examples of a consecutive sample is when companies/ brands stop people in a mall or crowded areas and hand them promotional leaflets to purchase a luxury car.
  • In this example the people walking in the mall can be considered as samples, let us consider them as representative of a population.
  • Now, these people are handed over an advertisement or a promotional leaflet and a few of them agree to stay back and respond to the questions asked by the promotion executive (we can consider him/her as a researcher).
  • The responses are collected and analyzed, but there is no conclusive result that people would want to buy that car based on the features described in the leaflet.
  • The promotion executive now asks questions to another group of people, who analyze the details of the car and its features and show a keen interest in buying the luxury car. Thus, this group of people has provided conclusive results for buying the car.

However, there is a downside to this sampling method. The sample cannot be considered as representative of the entire population. In the context of this example, not all people who have taken this leaflet were interested in buying the car.

Here is where sampling bias comes into the picture. So to overcome this bias consecutive sampling should be used in tandem with probability sampling.

Learn more: How to Determine Sample Size for your Next Survey

Advantages of Consecutive Sampling

  • In consecutive sampling technique, the researcher has many options when it comes to sample size and sampling schedule. The sample size can vary from a few to a few hundred, that the kind of range of sample size we are talking about here.
  • In this sampling technique, sampling schedule is completely dependent on the nature of the research, a researcher is conducting. If a researcher is unable to obtain conclusive results with one sample, he/she can depend on the second sample and so on for drawing conclusive results.
  • In consecutive sampling, a researcher can fine-tune his/her researcher. Due to its repetitive nature, minor changes and adjustments can be made right at the beginning of the research to avoid considering research bias.
  • Very little effort is needed from the researcher’s end to carry out the research. This technique is not time-consuming and doesn’t require extensive workforce.  

Learn more: How to Conduct Quantitative Market Research

Disadvantages of Consecutive Sampling

  • This sampling method cannot be considered as a representative of the entire population. The only way this sampling technique can get any closer to representativeness is by using a large sample size that represents a population.
  • Since there is a disadvantage of a sample obtained cannot be randomized, results or conclusions drawn through this sampling technique cannot be used to represent an entire population.

Learn more: How to Conduct Qualitative Market Research

Learn more about the other Non-Probability Samling Techniques: