Free Random Sampling Essay Example
Carrying out a survey sometimes can be very costly especially when it involves a large group of people or a big unit in a population. It will require a lot of resources both time and money. This is because you may need to train interviewers if the survey to be carried out involves a lot of complex questions. It is for this reason that some methods and frameworks have been devised to help in data collection by just taking a sample which is then used to represent the entire population (Sugano, 2013). Random sampling is one of such methods used in statistics to collect data through a survey. This method gives an equal opportunity for each item to be chosen to be part of the sample from the population. This equal opportunity ensures that there will be no biasness in the selection process of the items that will take part in the survey (Lemeshow et al., 2013). There are five general techniques for carrying out random sampling, namely; cluster, stratified, systematic, simple and multi-stage sampling.
Random sampling has many advantages over other sampling techniques. The importance of random sampling is due; it is simple and easy to use. The main advantage of using this method of sampling is that getting the sample is very easy, it is also cheap to use since it does not require a lot of steps and procedures. All one needs is to identify the target population for survey and then from the population pick a sample for analysis. This sampling method is also considered by many researchers to be one of the fairest ways of identifying a sample that will give a clear representation of the entire population because it gives every member or item from the population an equal opportunity of being selected (Sugano, 2013). So in this method, there are very low chances of biasness because there is no particular group that will be favored in selection of the sample since selection is random. Conclusions made from a research in which random sampling has been employed is always clear and reliable representation of the entire population because of its unbiased nature in selection of samples.
Another importance of random sampling is that the sample results of data collected by researchers can be analyzed easily using the readily available statistical methods (Lemeshow et al., 2013). Therefore, determining the relevant information from the research data e.g. the mean, mode and confidence levels can easily be established by just using statistical methods of analyzing data. However, when we use other methods of sampling other than random sampling, it will not be possible to use these statistical methods to carry out an analysis of data collected, thereby finding results and drawing clear conclusions. The major objective of carrying out a research would not be easy. Random sampling is suitable for use in sampling small populations.
Despite the above mentioned importance of random sampling, it also has its own shortcomings and limitations. For example, for one to carry out random sampling effectively, he/she will first of all need to come up with a full updated record of all the individuals or units of the population. Obtaining such records may not be easy when dealing with a large population, in such a scenario; it is always advisable to use other sampling methods to carry out your research (Lemeshow et al., 2013). Another limitation of this random sampling technique worth noting is that there is a possibility although minimal of a particular group to miss in the sample thereby reducing the full representation of the population and results in what is described as sample error. This limitation can however be overcome by subdividing the population into smaller groups, and then pick a sample from each of the groups so as to make sure that all the groups are represented. And lastly, this method of sampling can be limited in that it may not be the best method for researchers who seek to find information about a specific sub-group within a population; this challenge however can be solved by using stratified sampling.
Adam Sugano. (2013). The importance of random sampling in statistical experiments - Marketing Forward. Retrieved from http://www.experian.com/blogs/marketing-forward/2013/04/02/the-importance-of-random-sampling-in-statistical-experiments/
Levy, P. S., & Lemeshow, S. (2013). Sampling of populations: methods and applications. John Wiley & Sons.