This sampling technique [3] gives the researcher limitless chances of fine tuning his research methods and gaining a vital insight into the study that he is currently pursuing.

Difference of Sequential Sampling From All Other Sampling Techniques

If we are to consider all the other sampling techniques in research, we will all come to a conclusion [4] that the experiment [5] and the data analysis will either boil down to accepting the null hypothesis [6] or disproving the null hypothesis while accepting the alternative hypothesis [7].

In sequential sampling technique, there exists another step, a third option. The researcher can accept the null hypothesis, accept his alternative hypothesis, or select another pool of subjects and conduct the experiment once again. This entails that the researcher can obtain limitless number of subjects before finally making a decision whether to accept his null or alternative hypothesis.

Advantages of Sequential Sampling

• The researcher has a limitless option when it comes to sample size and sampling schedule. The sample size [8] can be relatively small of excessively large depending on the decision making of the researcher. Sampling schedule is also completely dependent to the researcher since a second group of samples [9] can only be obtained after conducting the experiment to the initial group of samples.
• As mentioned above, this sampling technique enables the researcher to fine-tune his research methods and results analysis. Due to the repetitive nature of this sampling method, minor changes and adjustments can be done during the initial parts of the study to correct and hone the research method.
• There is very little effort in the part of the researcher when performing this sampling technique. It is not expensive, not time consuming and not workforce extensive.

Disadvantages of Sequential Sampling

• This sampling method is hardly representative of the entire population. Its only hope of approaching representativeness is when the researcher chose to use a very large sample size significant enough to represent a big fraction of the entire population.
• The sampling technique is also hardly randomized [10]. This contributes to the very little degree representativeness of the sampling technique.
• Due to the aforementioned disadvantages, results from this sampling technique cannot be used to create conclusions and interpretations pertaining to the entire population [11].