Statistics - Assignment Example

Random sampling affiliation Introduction Random sampling is a method whereby every member of a population has an equal and independent chance to be selected in any study (Kothari 2011).Importance of random samplingRandom sampling helps to do away with the effects of unobserved factors like age, race, gender and even nutrition. For example, if somebody wants to calculate the average heights of persons in a city then he/she shall omit some of the unobserved factors like race and age among others.

It is unbiased since every member of the population is given an equal opportunity to be selected as a participant in the study therefore eliminating systematic bias. In essence, random sampling provides a simple way of choosing study participants from a large sample population in a fair way. Another significance of random sampling is that it plays as a representative of population of the study. The unbiased rule in simple random sampling makes it a vital method of drawing a conclusion from the study results, which is usually the main goal of a research.

Moreover, this sampling technique helps to make generalization of a particular population from the results obtained. Limitation of random sampling While using random sampling technique, it is always imperative to have a complete list of the study participants so that the researcher can make a sample from. However, this is often difficult to perform while dealing with a large population since the list must be complete and up to date, a condition that is difficult to meet. Random sample is not an appropriate technique to use while dealing with a very small sample size because the margin of error is usually wide, leading to a wrong conclusion (Medhi 2012).

The above problems can be overcome through using an average sample size of the population since it will limit the margin error incurred during random sampling.ReferenceKothari, C. R. (2011). Research methodology: Methods & techniques. New Delhi: New Age International (P) Ltd.Medhi, J. (2012). Statistical methods: An introductory text. New York: Wiley.