Explain The Importance Of Random Sampling

Explain The Importance Of Random Sampling. What problems/limitations could prevent a truly random sampling and how can they be prevented?

Random Sampling

Random sampling is a method of arriving at a sample size through randomization where each possible participant in the study and within the target population has an equal chance of representation in that any member can be selected through the random element. It comes in two broad ways: non-restricted random sampling and restricted random sampling. Simple random sampling is the most common type of non-restricted random sampling while others include lottery method and the table of random numbers where random number generators are used. In the category of the restrictive random sampling there are methods such as stratified sampling where the researcher uses the available information and attributes about the population to create rule for selection and inclusion into the participants set. Each of these categories of random sampling has their own outstanding merits and demerits that make them to be used in a particular occasion or be avoided in another study. Nevertheless, just by the fact that they all belong to the main category of random sampling, they enjoy some common advantages and suffer common demerits.

Importance of random sampling

The greatest benefit of random sampling is its simplicity. Gupta (2011) clearly brings out this point by arguing that random sampling is not dependent upon the existence or availability of detailed information about the population or the universal set for its effectiveness to be achieved. With this simplicity comes another advantage that touches on the flexibility of the method in allowing the researcher to introduce a degree of system or procedure into the random selection process to come up with various types and approaches of random sampling. For this reason, it is possible for a researcher to introduce a little restriction into the simple random sampling process and make it a stratified random sampling because of the flexibility and simplicity of random sampling. Random sampling has the least bias of the sampling techniques.

The reason a sample is selected is to have a proportionate representation of the entire target population. This is the area that random sampling gains strong grounds in that it ensures population is equally sample hence higher assurance of equal representation of every member in the population (this is because the method has no subjectivity). In addition, random sampling provides essentially unbiased estimates that also have measurable precision. Lastly, random sampling allows for possibility

Demerits of Random Sampling

Random sampling can sometimes lead to poor representation of the entire population especially if the population to be represented is extremely large and compounded by the fact that some random sampling procedures depend on random number generation which may leave out considerably large areas of the area to be covered (Martens 2009). Some practical constraints such as time availability and accessibility might hinder inclusion of some members or areas of study. Therefore, inaccessibility and time constraints can lead to lack of proper random sampling. Additionally, random sampling requires high level of skill and experience for its effective use.

To mitigate these problems and ensure that randomness is achieved as desired, time must be devoted to planning the entire process. The researcher must also solicit for experienced and skilled individuals to carry out the exercise of planning and execution of the process.

References:

Gupta S., P. (2011) Statistical Methods. Sultan Chand & Sons Educational Publishers: New Delhi, India

Martens, D. M (2009). Transformative Research and evaluation. New York: Guilford

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