Variety of Sampling Techniques in Thesis Writing

Sep 24 12:37 2015 Rohit Kaushik Print This Article

Sample quantifies the study into crisp and precise form by selecting any specific number of units under research rather the whole lot of population.

As all the population is not applicable in researching thus only a small unit of population is selected that represents the actual population. Choosing correct sample and its size are equally tricky and critical which can either result into a successful research or a fall short attempt in all. Consequently,Guest Posting you have been a researcher should first work on the sample size from the sample demographics that includes age, sex, educational level, religion, occupation or similar class association of population. So let’s go through some sampling techniques that can give real meaning and true sense of research to the thesis -

1. Random or Probability Sampling Technique– This is used when the size of the population is very large and it is comprised of a wide variety of categories in it. It solvates sampling error as in random selection almost all the categories of samples are taken also it gives most appropriate result of research. It is sub-divided into systematic random, stratified random, cluster random and simple random sampling techniques.

  • Systematic random – Sample is randomly chosen and then individuals are selected at regular intervals in a systematic manner like every second member is selected among a population of 100.
  • Stratified random – Group based study is done in the stratified random sampling technique. Random selection of unit is made from every group and is then included in the final sample size.
  • Cluster random – Similar to the stratified technique in the cluster also population is divided into groups or clusters and then each cluster is studied individually in the research.
  • Simple random – It is the simplest and most direct method of sampling in which simply a direct random selection of the sample is done from the entire population.

2. Nonrandom or Non-Probability Sampling Technique – All the unit in the population does not have equal opportunities to get selected in the sample as this is done in a planned and subjective manner. It includes straight and clear selection method. Subdivisions of non random technique are-

  • Judgment sampling – This is done when the researcher is confident enough about the sample and its authenticity.
  • Snowball sampling – This is done when a sample is rarely found. It is based on recommendations.

Hence, all the above discussed techniques require a thorough and in-depth knowledge of your thesis.

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Rohit Kaushik
Rohit Kaushik offers top notch PhD Thesis Writing Services, Proposal Help for doctoral candidates of UK Universities.

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