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Teaching Since: May 2017
Last Sign in: 225 Weeks Ago, 4 Days Ago
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  • MBA (IT), PHD
    Kaplan University
    Apr-2009 - Mar-2014


  • Professor
    University of Santo Tomas
    Aug-2006 - Present

Category > Numerical analysis Posted 13 Sep 2017 My Price 10.00

a method in which all members of a group (population or universe)


Random sampling is a method in which all members of a group (population or universe) have an equal and independent chance of being selected. It’s one of the most popular types of probability sampling. In this technique, each member of the population has an equal chance of being selected as a subject. There are many methods to proceed with random sampling: the most primitive and mechanical one would be lottery method. Another way would be to let a computer do a random selection from the population (Liu, H., Sadygov, R. G., & Yates, J. R. 2004).

 The importance of this method includes:i. It is easy and accurate method of representation as no easier method exists to extract a research sample from a larger population.ii. It is considered as a fair way of selecting a sample from a given population since every member is given equal opportunities of being selected.iii. Yields a sample that is representative to the group being studied.iv. It only needs a minimum knowledge of the study group or population in advance.v. It is free from errors in classification.vi. It is totally free from bias and prejudice.

Random sampling also inherent various drawbacks which are:1) The process may cost the individual a substantial amount of time and capital as it takes time to gather the information from various sources.2) When a sample set of the larger population is not inclusive enough, sample selection bias may occur.3) The selection of sample becomes impossible if the units or items are widely dispersed.4) It cannot be employed where the units of the population are heterogeneous in nature.5)  It may be impossible to contract the cases which are very widely dispersed.6) It lacks the use of available knowledge concerning the population.

  In conclusion, the methods limitations can be prevented by, keeping in mind that the list of the population must be complete and up-to-date to ensure effective sampling. A random sampling requires a complete list of all members of the target population so that the sample is a real representation of the larger group. Finally, no matter how large the population is, if it is not based on the random method the results will not represent the population that the researchers wants to draw conclusions about. To avoid this ensure that you first check to see how they were selected , look for the random sample, dig further into fine print to see the sample that was actually collected and use the preceding definition to verify that the sample was, in fact, selected randomly( Riffe, D., Aust, C. F., & Lacy, S. R. 1993).

ReferencesLiu, H., Sadygov, R. G., & Yates, J. R. (2004). A model for random sampling and estimation of  relative protein abundance in shotgun proteomics. Analytical chemistry, 76(14), 4193- 4201.

Riffe, D., Aust, C. F., & Lacy, S. R. (1993). The effectiveness of random, consecutive day and  constructed week sampling in newspaper content analysis. Journalism & Mass  Communication Quarterly, 70(1), 133-139.


Status NEW Posted 13 Sep 2017 09:09 AM My Price 10.00

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