Random sampling is important because it reduces time and cost of counting or measuring something in its entirety such as a large part of the population, a specific type of tree, or a specific breed of animal. Random sampling is also preferred for its ability to help reduce bias. A true random sample would be hard to obtain because all parts of the population need to be represented. Simple random sampling is achieved by random selection of members from the sampling frame. The random selection can be accomplished many different ways, the most common being a computer program to randomly select the sample (Grove & Cipher, 2017). Having a computer to randomly select the sample is great but is the computer going to be able to tell if any of the participants are on vacation, out of the area on business, or if they have language barriers and these are just some of the complications that could present a problem in the random sample. Another problem and/or limitation that could prevent a truly random sample is having too small of a random sample to use for a study of a large populous. Having too small a group to study will not show accurate data for a large populous. A way to prevent some of these complications would be to have an appropriate sized study group for the random sample, and to ensure that all parts of the population or demographics are represented.
Grove, Susan, K., & Cipher, Daisha, J. (2017). Statistics for nursing research: A workbook for evidence-based practice, (2nd) edition. (pp. 13). Elsevier Inc. Retrieved from: http://www.gcumedia.com/digital-resources/elsevier/2016/statistics-for-nursing-research_a-workbook-for-evidence-based-practice_ebook_2e.php
(2017). Why is sampling important?. Retrieved from https://www.reference.com/math/sampling-important-6d0178c3312c59db#