Sampling size and sample size for qualitative research - Coursework Example

There are many factors that divide the population into sub-populations. This study expects that the measurement of interest may vary significantly among different strata. The variation has to be captured when selecting a sample from the whole population in order to obtain a sample that represents the whole population (LeCompte & Schensul, 2010). This is very significant in eliminating any form of biasness. A stratified sample is obtained through taking samples from each stratum of the whole population.

As a result, each characteristic that is unique within the population which is under study is captured. This plays a significant role in reducing any potential for human bias when selecting cases to be incorporated in the sample (Ryan, 2013). Therefore, this strategy will enable me to come up with a sample that is highly representative, assuming that there will be no cases of missing data which might affect the overall results of the study. Reducing sampling error is one of the major goals of any selection technique while conducting a research.

Although other sampling techniques are less expensive and time consuming, they are bound to have several errors that might affect the overall results of the study. Therefore, the fact that each stratum is incorporated in the sample and all the variables that might affect the results are taken into consideration makes this strategy to be more effective in comparison with others. Since the samples are selected using probabilistic methods, stratified sampling method will enable me to make statistical conclusions after analyzing the data that will be collected.

This will be critical in identifying whether the data will be valid or not and whether there will be some other factors that will need to be taken under consideration. Furthermore, relative to simple random sample, this strategy is more superior because it will improve the potential for the units to be evenly spread across the