Last week, we went over qualitative research. Though
analyzing one’s research and thoughts establishes rich information, sometimes statistical
data or experimental results provide enough information to support a reasoning.
Quantitative research is defined as the idea where social phenomena can be quantified,
or measured and expressed numerically (Mamia, n.d.) .
Surveys, experimental results, and demographic statistics are examples of
numerical data that can be used in a quantitative research.
Unlike qualitative research, quantitative research aims to
answer why something happens or happened. Scientific reports provide good
examples of what makes up a quantitative research. Every research needs to have
some sort of idea: such as an actual thought or a guess. For a scientific report,
you may have a rough idea on a result, but you usually start off with a hypothesis,
or a guess. These parts of the scientific report is similar to the first four
parts of the research process. The next step of the research process is to
establish a research design. For the scientific report, this will be equivalent
to establishing and determining how the experiment will be conducted. This may include
what materials are required, the measurements of the materials, and identifying
the variables involved during the experiment. Once everything is clear and
ready to go, data collection can be made. After the collection of data, we then
analyze the data. Numbers itself doesn’t provide enough information to support
your ideas, so it is important to proceed to the next steps of the research
process: answering empirical research questions, making theoretical
interpretation of the results, comparison with earlier research (maybe
comparing with the founder of a scientific phenomenon) and making a conclusion.
Similar to my last post on qualitative research, this has a
tie with systems of thinking. Personally, I believe the key concept of
quantitative research is to transform body of knowledge, or a cluster of information
into something meaningful and clear. As previously mentioned, numbers itself
doesn’t provide enough information. Though they look reliable at first view, it
is important to understand and explain what these numbers represent and how it
relates to your topic. As we analyze data, we are gaining understanding and
making sure that our ideas are accurate and strong.
Sources
Hill, T. W. (n.d.). Scientific Reports.
Retrieved from The Writing Center at UNC-Chapel Hill:
http://writingcenter.unc.edu/handouts/scientific-reports/
Mamia, T. (n.d.). Quantitative Research Methods:
General Studies/ISSS. Retrieved from
https://erau.instructure.com/courses/34959/files/5407384/download?wrap=1
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