Sampling strategy

Sampling strategy for a research on learning disability

Sampling strategy

In order to conduct an effective research efficient sampling strategy formulation possesses crucial significance. To increase the authenticity of the information effective sampling strategy should be formulated (Healey, 2008). The main purpose of effective sampling strategy is to reduce the margin of error, the margin of error is also defined as “Beta ß” (Nachmias, 2008). If the margin of error is minimized the data will yield authentic results. Effective sampling strategy requires vigilant selection of population, proper sampling technique and percentage of sample drawn from population.

Reasons for choosing the strategy

The sampling strategy for this research is the probabilistic sampling strategy. The reason for selecting this strategy is because the probabilistic sampling strategy provides equal chances to every entity to be selected in the sample size. Probabilistic sampling minimizes the biasness and other factors that could affect or manipulate the data acquired through research. This will ultimately lead to more accurate and authentic results. This is the reason for choosing probabilistic sampling strategy.

Sampling strategy for quantitative research

There are two main categories of sampling strategies that have been identified. These strategies allow researchers to select the sampling technique which can best serve the interest of the researcher and suits the nature of the research. Selection of proper sampling strategy minimizes the standard of error in the data and provides authentic results. There are two categories of sampling strategies; probabilistic sampling and non-probabilistic sampling (Kendrick, 2004). In the strategy known as probabilistic sampling the sample is randomly drawn from the population, in this type of sampling researcher cannot act biased and every entity comprising the population holds equal probability to be included in the sample. This sampling technique comprises simple random sampling, stratified random sampling, systematic sampling and cluster sampling (Nachmias, 2008). However, in contrast the other sampling procedure is known as non-probabilistic sampling, this procedure gives authority to researcher to select his sample size on the basis of his judgment. In this procedure not all entities of the population have equal probability to be selected. Non-probabilistic sampling includes quota sampling, convenience sampling and purposive sampling. The strategy that best serves the interest of a quantitative research is probabilistic sampling because the data collected through this procedure has more confidence level due to non-biasness as compared to the non-probabilistic procedure and hence provides authentic results (Nachmias, 2008).

Population of the study

The prime objective of this research ...