Quantitative
Journal Research Methods
The quantitative
research methods in social science reviewed here are sourced from Karl Von Bround book titled "The Practice of Economic Research Journal". Quantitative
research methods use numerical data and emphasize the research process on
measuring objective results using statistical analysis. The focus of the
quantitative method is to collect data sets and make generalizations to explain
the specific phenomena experienced by the population.
Why do
quantitative research?
The purpose of
quantitative research is to determine the relationship between variables in a
population. There are two kinds of quantitative research designs namely
descriptive and experimental. Descriptive quantitative studies take
measurements only once. This means that the relation between the variables
investigated only takes place once. Whereas experimental studies measure
between variables before and after to see the causal relationship of the
phenomenon under study. Next will be presented the characteristics of
quantitative research.
What are the
characteristics of quantitative research?
The data
collection process is carried out using structured instruments, such as
questionnaires, survey sheets or polls.
The results of
the analysis are based on samples that are representative of the population.
The same study
can be repeated in the future to achieve a high level of reliability or
confidence.
All aspects
needed for the study have been prepared carefully before the data collection
process, including research instruments.
Data in numeric,
numeric or statistical form
Researchers use
analytical tools such as computer software to process data.
The main
orientation of quantitative research is to classify, calculate, and construct
statistical models to explain what is being studied.
Quantitative research
prioritizes data objectivity in studying a social phenomenon.
In quantitative
research, data sets are collected, processed and analyzed to find the
relationship between the variables studied. The variable used can be two or
more. In social science it is usually more than two because variables are
always in complex social settings. For example, we will examine the
relationship between residence and income. The hypothesis that is built is, urban environments
have opportunities for higher incomes. In fact, high income is not determined
solely by place of residence. There are other variables that are very possible,
for example the level of education, heredity, and so forth. The consequence of
quantitative research is that relations between variables can be statistically
significant, but socially insignificant. Then what are the advantages of
quantitative research methods and what are the shortcomings?
quantitative
research methods
The following are
some advantages and disadvantages of quantitative research methods.
Strengths of
quantitative research methods:
◊ Supports social
science studies that are macro in scope because they can involve a large number
of research subjects. The number of subjects both individuals or groups
involved support the generalization process.
◊ Have capital to
achieve objectivity of research results. In general, quantitative research is
designed to produce general or general explanations of a phenomenon. To get
this general explanation, several variables are used.
Ampu Able to
apply the average number of a calculation so that the research design can be
replicated and analyzed for relevance elsewhere.
◊ Able to carry
out comparative study objectively.
◊ The potential
for personal bias can be avoided by the researcher keeping a distance from the
participants being studied and by using computer software when analyzing.
Weaknesses of
quantitative research methods:
◊ Often ignores
details of the social context under study.
◊ The approach is
static and rigid so it is not flexible when researchers are in the field.
◊ Has the
potential for structural biases because the formulation of the problem made
usually reflects the interests of researchers without considering the actual
problems faced by participants.
◊ Research
results are often lacking in detail in explaining individual behavior and
motivational actions.
◊ Researchers may
collect data that is narrow and superficial in scope.
◊ The results of
the study have a limited explanation of the quality of numerical descriptions
and lack of detail in elaborating aspects of human perception.
◊ Research
results tend to describe the results of laboratories rather than the real
results of what is happening in the field.
quantitative
method
Basic framework
for quantitative research
In essence there
is no quantitative research framework or design that is considered the most
correct. The research framework is always flexible, the most important thing is
to be systematic and maintain the research substance. However, there are always
elements that form the basis of research design. For example, the formulation
of the problem. There is no research without problem formulation. The following
basic framework is commonly used in quantitative research quoted from the book
"Doing Quantitative Research in the Social Sciences: An Integrated
Approach to Research Design" written by Thomas R. Black:
preliminary
Introduction to
quantitative research generally contains background research. Information in
research also includes:
Problem
formulation: In this section the researcher states clearly what problem he
wants to investigate. The formulation of the problem form is usually in the
form of a question sentence or it can also be a statement containing questions.
The formulation of the problem when translated into English is the
"research question".
Literature
review: The researcher reviews some academic literature that is considered
relevant to the topic, then synthesizes it. If necessary, the researcher
records any literature whose methodology is similar for future comparison and
reference. It also needs to be explained in this section, how the research
carried out contributes to the shortcomings of existing research.
Theoretical
framework: The researcher describes the theory used or the research hypothesis.
If needed, the researcher also describes theoretical terminology that is
difficult to understand to help the reader understand the background of his
research. Generally quantitative research explains what the hypothesis is
rather than what the theory is.
Methodology
In this section,
the researcher must explain the purpose of his research and how that goal can
be achieved. An explanation of the methodology used will help the reader make
an assessment of the quality of his research. The more detailed the information
provided the better. The methodology section also includes:
Population and
sampling: The researcher explains where to get the data used. Is the data
discarded or excluded? If so, why?
Data collection:
Researchers describe the process of data collection and identify the measured
variables. It needs to be emphasized whether the data obtained is already
available data or researchers are looking for themselves, for example by
survey. Because there are no perfect data sets, limitations or limitations in
data collection methods also need to be described here.
Data analysis:
Researchers describe the process of data analysis clearly. In general,
decryption of statistical calculation techniques and software used are also
displayed in this section.
Research findings
or findings
Penalty findings
must be written objectively. In quantitative research, it is common for
researchers to display research results visually with graphs, tables, or
diagrams to help readers understand data easily. But it should be underlined
that visual data is a supplement to the textual description that is displayed.
In this section, researchers provide:
Statistical
analysis: How are the data analyzed and what are the findings? Findings are
descriptions of data displayed textually and / or visually. Be careful in
describing, lest the researcher interpret the findings. An interpretation of
the research findings is presented in the next section.
Discussion
In contrast to
descriptive research findings, the discussion section must be analytical,
logical and comprehensive. This section is a meeting between finding data and
data from the literature used. The discussion section includes:
Data
interpretation: Researchers interpret data findings. When interpreting, the
researcher presents the problem formulation and the hypothesis. The important
questions are whether the interpretation of the findings answers the problem
formulation, and whether or not accepting hypotheses that were built
previously. Two answers to that question need to be written here.
Describe trends
and relationships between variables: Researchers need to describe trends based
on their findings. An explanation of non-significant statistical correlations
also needs to be described.
Implications:
Researchers describe the implications of the results of their research. What
the research findings are also displayed again in short sentences to convince
readers that the findings are very important and able to answer the problem
formulation.
Limitation: The
researcher describes the bias in this section because there are no quantitative
studies, also qualitative perfect without bias.
Conclusion
In this section,
the researcher concludes his study with a brief conclusion related to the theme
of his research, followed by comments and final assessments. The concluding
section includes:
Conclusions of
research findings: Researchers describe the answers to the formulation of the
problem. Keep in mind that statistics should not be displayed here again. But
the narrative about the findings needs to be rewritten in a concise or in
essence version.
Recommendations:
Researchers write recommendations if their research contributes to policy
formulation. The recommendations written must always be based on the findings.
Follow-up
research agenda: The research agenda offered must be based on previously
written study limitations.