Quantitative Journal Research Methods


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.