Difference between Qualitative and Quantitative Research Sampling Strategies

This article discusses the difference between qualitative and quantitative research sampling strategies and their advantages and disadvantages. It also explores the importance of appropriate sample size determination in research.

Running head: STATISTICS 1
Topic: Statistics (Research in Nursing)
By (Name of Student)
(Institutional Affiliation)

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The difference between qualitative and quantitative research sampling strategies
Qualitative research sampling strategies are the primary exploratory researches which
are used in gaining the understanding of the underlying opinions and reasons which help in
developing the ideas or hypotheses for the potential quantitative research (Bernard, 2017).
Quantitative research strategies on the other hand are research sampling strategies that are
used to quantify the given problem by the method and approach of generating numerical data
that can be useful in statistical and social fields.
Unlike the quantitative sampling strategies, qualitative sampling strategies are used to
uncover the trends in thoughts and opinions. In relation to the data collection techniques, both
qualitative and quantitative research methods vary using structured and semi-structured
methods of data collection like online surveys and paper surveys (Brannen, 2017).
Advantages and disadvantages of each strategy
i. Qualitative Research Sampling Strategies
Advantages Disadvantages
i. It avoids research findings from
being artefacts of the method
being applied.
ii. Allows focus upon hidden
aspects of the organizational life
iii. When well done, it enables
greater understanding of the
organizational processes and
events (Neuman, 20130.
i. The research is not always
detached from what is being
studied.
ii. Entails long periods in the fields
iii. Not easily replicable

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ii. Quantitative Research Sampling Strategies
Advantages Disadvantages
i. Permits formulation of
statistically sound hypotheses
with no room for the emotional
design.
ii. Time consuming manual
implementations of ideas can be
automated and hence performed
exponentially.
iii. Enables evaluation of multiple
datasets and hypotheses, faster
and more accurately than any
human brain could ever perform.
i. Requires constant monitoring of the
model performance to ensure
continued compliance with the
original hypotheses.
ii. Inadequate quality of training data
used in the model construction can
lead to erroneous or even disastrous
model performance on the unseen
data.
iii. Requires deep background in the
multiple complex disciplines that are
hard to master for the average
person.
Appropriate sample size determination by the researcher
` A sample can be defined as the proportion/part of the population that is used by the
researcher in making inferences about the whole population of the study. Better or
appropriate size of the sample is needed to ensure that the researcher makes a better
inferences and conclusions about the population under the study. For instance if the topic
under the study is “Women and Substance Abuse”, the research should consider taking
average sample size of 200. This is a relatively large sample size leads to better results and

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inferences. Also, the research may apply appropriate formula to determine the best sample
size. This is done when the whole population size is known (Richard, 2013).

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References
Bernard, H. R. (2017). Research methods in anthropology: Qualitative and quantitative
approaches. Rowman & Littlefield.
Brannen, J. (2017). Mixing methods: Qualitative and quantitative research. Routledge.
Neuman, W. L. (2013). Social research methods: Qualitative and quantitative approaches.
Pearson education.
Richard, T. (2013). Qualitative versus quantitative methods: Understanding why qualitative
methods are superior for criminology and criminal justice. New Times