Importance Of Sampling, Pretesting, And Validity In Research

Sampling Techniques: Randomized vs Non-randomized

The post by Lacie Gordon on manage discussion entry gives an analysis of how surveying of the individuals give allowance for the trends, beliefs and mental outlook for quantitative analysis. According to the post, randomization is chosen as a way to control the experiment for the access of factors in studying the results of the study.  The post states that the nonrandom sampling technique gives the name “quasi-experiment” meaning the participants are not chosen in a random way and therefore, the probability of being chosen is very minimal. In the post, the fact on non-sampling being often chosen since it is convenience fulfills the quotas of the researchers (Parker, 2011).  Lacie Gordon in the post states clearly that samples are essential since they categories results in an impartial research. The post gives the general individual inclusions such as groups and features equally viewed.  Based on the post, pretesting, field testing and pilot testing are very necessary for demonstration of content validity and their scores.  Reflecting on the post non-response type of bias occurs in the case whereby the contributors do not respond to the questionnaire (Morgan, 2014). And lastly, every person’s life has an understanding that we are not equal. This is well illustrated by the fact that different people have different height, weight, and age and therefore its responsibility of the researchers determine the disparities ways of measuring the data.

The Tara Thomas post on manages discussion entry gives support for a better understanding of the how quantitative and qualitative methods are applied in the research sector.  The post gives that analysis of differences between the nonrandomized and randomized approach of sampling in population. It also discusses the role played by sampling technique when conducting a research. Based on the post, random is categorized as part of the sampling method where the samples are chosen in a probability manner (Bloomberg & Volpe, 2008). This method is not biased according to Tara Thomas post. The Tara Thomas states that the samples represent the total population and if otherwise, then this is what is called sampling error. If there any sampling errors, the researchers need to choose the nonrandomized method of sampling. This is alternative method aimed at selecting samples on the basis of hypothesis interest of the population (Kuckartz, 2014). Based on the post, it is well known as selection criteria. For instance, if stopping people is a way of collecting the samples, any attempt to stop the same number of both men and women is what we can refer to as nonrandom sampling. The role of sampling in a research is to get accurate results in research.

References

Bloomberg, L. D., & Volpe, M. (2008). Introduction to your study.In Completing your qualitative dissertation: A roadmap from beginning to end (pp. 32-44).

Kuckartz, U. (2014). Chapter 1: Analysing qualitative data—But how? In U. Kuckartz, & A. McWhertor (Trans.) Qualitative text analysis: A guide to methods, practice & using software (pp. 1-14)

Morgan, D. L. (2014). An introduction and overview. In Integrating qualitative and quantitative methods: A pragmatic approach (pp. 2-24).

Parker, J. (2011). Chapter 3: Best practices in quantitative methods teaching: Comparing social science curricula across countries. In G. Payne, & M. Williams (Eds.), Teaching quantitative methods: Getting the basics right (pp. 32-48).