SOC 333 Research Methods: Week 4 Discussion on Qualitative Data

This document presents a student's responses to discussion posts for SOC 333 Research Methods, Week 4. The responses analyze the concepts of sampling techniques, differentiating between randomized and non-randomized approaches in research. It highlights the importance of randomization in controlling experimental factors and addresses the limitations of non-random sampling, also known as quasi-experiments. The discussion covers the role of sampling in ensuring impartial research results, the necessity of pretesting, field testing, and pilot testing for content validity, and the potential for non-response bias in surveys. Additionally, the responses emphasize the significance of understanding individual disparities in data measurement and the application of both qualitative and quantitative methods in research.

Running Head: SOC 333 Research Methods week 4 post response
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SOC 333 Research Methods week 4 post response
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SOC 333 Research Methods week 4 post response
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Post 1 response
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.
Post 2 response
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

SOC 333 Research Methods week 4 post response
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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.

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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).