Population and Sampling Distributions
Introduction
At first we shall begin with the definition of sampling, it refers to the collection of the subset of individuals from a particular population with the aim of coming out with an estimation of the features of the whole population. We then narrow down to the definition of random sampling which refers to the method of selecting a sample from a particular statistical population in a way that it adopts the use of probability, (“What is Random Sampling? – Definition, Conditions & Measures – Video & Lesson Transcript | Study.com”, 2016). In this case, the sample is not predetermined but a general assumption is done.
Importance of random sampling
Random sampling is important in statistical research as a key element of preventing or removal of bias in the results. It allows for a selection without interference of an individual thus impersonal choice. In this case, an individual carrying out the sampling procedure or the sampler will have no choice in determining the sample to be used thus also a representative of the whle population. In case the sampler is involved in the process, true sampling will not have been carried out thus bias tolerated.
Problems/limitations for random sampling
In daily activities involved in carrying out statistical research using random sampling, there difficulties encountered which prevents random sampling from being achieved. The major one is the inability to obtain the full list of members in a population in order to get a sample. At times, some members may not be included thus non-viable results. The second limitation is biased results and the laborious nature of random sampling.
Sampling techniques
- Stratified Sampling-this is where a researcher divides the population into separate groups then a random selection is done from any of the groups an example is in the use in polling elections, (Explorable, 2016).
- Cluster Sampling-this is where the total population is divided into clusters and a random group is selected. Example is coming out with a market research for products, (Explorable, 2016).
- Systematic Sampling- this is where the sample members from a larger population are as per where they started until the finish point by using an interval. An example is the use of eg coming up with a linear progressive formula, (Explorable, 2016).
- Simple Random Sampling (SRS)-this is whereby a sample is simply picked from a group of items without considering any requirement. An example is random voting taking place
References
What is Random Sampling? – Definition, Conditions & Measures – Video & Lesson Transcript | Study.com. (2016). Study.com. Retrieved 12 September 2016, from http://study.com/academy/lesson/what-is-random-sampling-definition-conditions-measures.html
Explorable (2016). Explorable.com. Retrieved 12 September 2016, from https://explorable.com/statistical-sampling-techniques
