Sampling Quantitative Techniques For Data analysis

At Statswork, our experts help you to identify right sampling technique for your research work.

Sampling:

Sampling is a significant process in your business research or your academic research that plays a vital role in simplifying your complete data collection work. Samples are extracting from the population. Hence, the sample has the features of population. Samples are reduced based on the time and cost. Based on the theorem, it is noted that the ‘Sample mean is an unbiased estimate of population mean’. Our Statswork experts are well aware of the sampling techniques prevalently used and we suggest you the best sampling method for your study.

Several types of sampling techniques are available as follows:

Random Sampling:

This is the easiest form of probability technique. In this method, each and every respondent will get equal chances. However, if the target population is high then it is very difficult to define the exact sample size (Saunders et al., 2003).

Systematic sampling:

This method is commonly referred as the Nth name selection method. In this method, each and every Nth record can be selected from the target population (Saunders, 2003).

Stratified sampling:

Based on the characteristics, the research will classify the research population. After that the participants will be selected by the researcher from (Saunders, 2003).

Convenience sampling:

In this method, a subset of participants will be selected by the researcher due to time and cost constrictions. This method often assumes that the target population is represented by the subset of population. In this method, subjects with convenient accessibility are generally selected by the researcher (Saunders 2003).