Research Methods in Social Science: Quantitative vs Qualitative

This article discusses the differences between quantitative and qualitative research methods in social science. It covers the related philosophy, data collection approaches, data analysis techniques, and comparisons between both methods. The article also highlights the benefits and disadvantages of each method.

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Running head: RESEARCH METHODS IN SOCIAL SCIENCE
Research methods in social science
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Researchers in social science adopt two major research methods that are related to two
distinct philosophies. The conduct either the quantitative method of research in relation to the
positivism philosophy or to adopt the qualitative method of research related to the interpretivism
philosophy (Rahman, 2017). Different arguments do exist between the two approaches
concerning the superiority of the research method. The following section discusses in details the
two research methods, including the definitions, related philosophy, the approaches of data
collection related to each of them, thematic analysis, data analysis techniques and comparisons
between both of them.
The quantitative research process uses the numerical data and statistical methods to get
the research results. Questions like when, where, who, how many and when are asked by using a
certain data analysis technique. Data has to be collected in order to be analyzed and to test the
research hypotheses. The quantitative approach begins by stating the research problem, then
formulating the hypotheses, then conducting a review of the related literature, then data
collection is conducted, followed by a quantitative data analysis. The quantitative research
depends on strategies of data inquiry as surveys (Apuke, 2017). The quantitative research could
be a survey research, correlational, experimental or causal-comparative research. The survey
research is the most widely used technique in data collection. It is a social scientific method for
data collection from a population. The sampling methods depend on questionnaires to measure
the characteristics of a certain phenomenon. People are asked about their opinions, attitudes,
behaviors and motivations (Tan & Runeson, 2017). The traditional surveys take the form of
close-ended questions as an interactive research strategy. The survey involves interaction with
the respondents in a minimal way. Variables are the characteristics used in describing the things

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with different quality and quantity. Variables could be measured, controlled and manipulated as
well. The independent variable is the manipulated variable to observe its effect on a dependent
variable (Tan & Runeson, 2017).
On the other hand, the qualitative research method is used in interpreting the social
interactions. The collected data in non-numerical as it could take the form of text, image or
videos (De Costa, 2017). The qualitative methods focus on the method used by the researcher in
collecting qualitative data. This method involves direct observation of the phenomenon of
investigation, interviews that could be done online or face to face and historical narrative (Smith,
2017). The qualitative method is considered a holistic research perspective that provides more
information about the phenomenon under investigation. It assists the researcher in delivering
data based on real knowledge (Shaheen, 2018). There also exists a combined way between the
quantitative and the qualitative methods. Mixing between the two methods could create a value
added to the research. The qualitative research is likely to add an in-depth detail to the research
to strengthen the research findings (Centellas, 2016; Creswell, 2013).
The quantitative data analysis includes the summary statistics, relationships between
variables, subgroup analysis, statistical methods, and trend analysis generalization of results to
the population. Variables could be classified into intervals based on predetermined rules, ordinal
or ranking method and nominal or categorical classification. Reporting quantitative data should
take the textual and visual formats as diagrams, tables and maps. The good organization of data
involves the use of visualization to enable the decision maker from identifying the trends (World
Health Organization, 2014). Data analysis is considered a crucial activity in the qualitative
research. The qualitative data analysis has a variety of aims, including the detailed description of

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a phenomenon. It could also be used to compare between cases and their common characteristics.
The analysis of the qualitative data usually comes after the field access. Decisions are made with
the guidance of data analysis status. Data could be analyzed according to the grounded theory
(Flick, 2013; Roth, 2015).
A good research has to be significant. It could represent a continuation of a previous
research within the same population. It could also be an extension of a previous research or
theory applied to the same or a new population. It might represent a new inquiry when it
investigates a new population or seeking to develop a new theory (Miles & Scot, 2017).
The research methodology assumptions determine the research methods and techniques
and the decisions related to them that in most cases is related to the researcher's utilization of
epistemology and ontology. In social research, no specific knowledge can assure by itself the
reliability and validity of the research results. Though, the research philosophy is important to
the researcher to understand the research process and the role they do in research in order to
develop a concrete theory and the body of knowledge (Xian & Meng-Lewis, 2018). In social
science, ontology refers to the real nature and its existence and epistemology refers to the nature
of knowledge. Therefore, ontology deals with the nature of the investigated social phenomenon
that already exists regardless of our knowledge of it.
On the other side, epistemology is about the way the researchers conduct to access the
truth in relevant to his way of understanding the world. Also, two views of epistemology exist in
social science research. The first is the objectivist or positivist versus subjectivist or
constructivist epistemology. The objectivity or positivist assumes that the researcher conducts a
neutral role in the research process without any subjective evidence. The subjectivist or

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constructivist view considers the researcher experience and their active engagement in the
research process with their personal understanding and knowledge. The ontological and
epistemological are considered as the foundation phase to the philosophical perspectives,
including, positivism and interpretivism (Bhattacherjee, 2012).
The quantitative research process depends on the positivist philosophy that adopts the
same philosophy of the natural science. It involves objective data collection to be used in
hypotheses testing. The researcher should not interfere his feelings to develop an objective
theory. Positivist is related to the objectivist epistemology that assumes the existence of a neutral
point at which the researcher observes the natural world in an objective way to know the truth.
On the other side, the qualitative research process depends on the interpretivism philosophy
argues that the positivist methods is not capable of capturing the experiences of the human
capital as the social activities are very complex. It also assumes that the human interpretation is
very important to the knowledge development. The interpretivists believe that subjectivist
ontology cannot separate the researcher from the reality. As the life experience of the observer
cannot be separated from the perceived reality as it the way of making sense in social life.
Interpretivists behave in a manner that reflects their culture, experience and history. Although the
information is unique, different individuals can interpret it in a different way and different
meanings according to the context that created the information. Interpretivism is related to the
qualitative research and the studies are usually conducted at a micro level to produce a detailed
description of a specific social phenomenon. Their results could not be generalized due to the
small number of observations that the research utilize. Working hypotheses are then to be
developed in order to describe an individual case that was researched (Bhattacherjee, 2012; Xian
& Meng-Lewis, 2018).

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The quantitative research process uses the deductive approach known as the top-down
approach that is related to the positivism. The researcher tries to disprove the hypotheses of the
theories rather than to prove them. The future of the phenomenon under investigation could not
be predicted by the past experience of the researcher. The process of deduction goes through five
steps, it starts by conceptualizing a framework or model, then hypotheses are to be formulated
and operationalized in a deductive logic about what should happen and the theoretical concepts
are to be tested through measurements. Data is then collected to test the hypotheses. When the
hypotheses are approved, the theory becomes a reality. In case the hypotheses are failed to be
approved, the theory should be adjusted (Bhattacherjee, 2012; Xian & Meng-Lewis, 2018).
The qualitative research process uses the induction which is a bottom-up approach, it
starts with the theory, then it uses data to build up the theory. Researchers who use the inductive
research depend on the real-life experience and practice to develop the theory. They also refuse
to rely on the literature in order to broaden their imagination and encourage the development of
new theories. The grounded theory is a famous method that allows theories to emerge from the
empirical data. The researchers that use the induction method believe in the interpretivism
philosophy and consider the human knowledge is critical for theory development. The inductive
approach allows for a flexible structure for a potential change of the research. The researcher has
to examine imperical data and provide an explanation for the phenomenon of interest during the
research development. The start point is the social phenomenon that is not related to any theory,
and assumptions are made to act as the theory boundaries. Observations are collected by the
researchers and at the same time, they apply the existing knowledge in the literature (Xian &
Meng-Lewis, 2018).

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Data analysis requires testing the quality and validity of data, including, treatment of
missing and extreme values. Detecting errors is easy to be done through visualization (Kandel et
al., 2012). According to Bihani & Patil (2014), data analysis techniques could be one of four
techniques represented in the descriptive analysis of data that aims to describe the business
situation through the clarification of the trends, patterns and expectations. The second technique
is the inquisitive analytics that uses the collected data to test the research hypotheses. The third
technique is the predictive analytics that uses the collected data to judge the future possibilities.
The fourth technique is the prescriptive analytics that mixes between the three analyses
techniques.
The thematic data analysis is used by researchers to analyze patterns of themes or
meanings. It is used in qualitative data analysis as an analytical method. It is not a theoretical
assumption or a data collection method, although it could be used in the theoretical frameworks.
It involves the important role of language and meanings and considers the patterned meaning in
the data set. It could be applied to almost all of the types of research questions considering the
population's opinions about a certain phenomenon in a certain context. It describes both the
implicit and explicit ideas (Ibrahim, 2012). It is used to analyze data collected from secondary
resources as the reports and books, textual data as a qualitative survey, interactive data as
interviews and naturalistic data as audio recordings. Data is coded and then the themes could be
identified. Themes are used to provide a structured presentation of results. In order to be sure of
the used coding system, the researcher calculates inter-rater reliability scores that require a
codebook to be developed (Duschinsky, 2014). The thematic analysis could also be used in the
quantitative data analysis or the theory-driven analysis that goes top-down. The thematic

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approach goes through six phases for both types of induction and deduction approaches
according to Clarke & Braun (2013), as follows:
 The process of familiarization with data through conducting several iterations of reading.
 Data coding that could be generated in relevance to the research questions. The codes
should be treated independently from data and the researcher should classify data
according to the codebook.
 The coded data is to be examined according to the themes to identify similarities.
Relationships between themes should be established by the researcher.
 The themes should then be reviewed in comparison to the coded data to assure a good fit
between them and between themes as well.
 An additional review of the theme according to the whole data set is conducted by the
researcher.
 The final phase is writing up the final report including data presentation and
visualization.
When it comes to comparing between the quantitative and qualitative methods of
research, we can find that both of the two approaches differ in the philosophy that articulates
each of them, the role of the researcher and the way data is collected and analyzed. A debate
occurs about the two approaches, as the statistical research is used in the quantitative research,
but not all the quantitative analysis is statistical. Also, it is possible to use the statistical methods
for the analysis of some qualitative data (Greener, 2008). Moreover, it is impossible to say that
one method of analysis is better than the other, as both of the two types has its advantages and
disadvantages and each of them could be used for a certain type of research question. It is also

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important to differentiate between the two methods and the type of data collection. Quantitative
data is related to quantities and amounts of things but the qualitative data is related to the quality
of things and it is recorded in a descriptive way (Webb, 2017). The existence of alternative
research approaches aims to promote the dialogue between them (Edwards & Brannelly, 2017).
The qualitative method of analysis has benefits represented in its ability to provide a
detailed analysis of the research results through the description of the interrelationships between
information processing performances. It could be used to study individual cases as it could
interpret people's feelings, voices and meanings. Finally, it allows the researcher to use his
practices and inner experiences. The disadvantages of the qualitative approach are represented in
its involvement in the descriptive details out of the main context. Also, its results are not
appreciated by policymakers as its results could not be generalized to the population. On the
other side, the quantitative approach has many advantages represented in the ability to generalize
its results to the population or a subgroup of it as it depends on large samples in most of the
cases. The data analysis process could take shorter time when compared to the qualitative data
analysis. It also guarantees the objectivity of the researcher as it is meant with theory testing.
Despite its advantages, it has disadvantages represented in the neglection of the social
phenomenon meaning. Also, the positivism does not investigate the way the reality is shaped.
Finally, it measures a limited number of variables at a specific time (Rahman, 2017).
We have to concern about ethical issues in research, as ethics should be considered in the
research methods to assure the use of accepted activities. The ethical policies should be involved
in the research, including, the honesty and integrity, objectivity, carefulness, openness by being
able to share the results with the society and accept their feedback, to respect the property rights

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of others and to protect confidential data and the participants' personal data and opinions
(Healey, 2017). It could be important that a research committee review the research before
disseminating its results to ensure the ethical aspects are considered. Also, it is important to the
researcher to consider that data collected for a certain purpose should not be used in another
purpose unless the researcher gets an ethical approval for using it (Harriss & Atkinson, 2011).
In conclusion, the social science, ontology refers to the real nature and its existence and
epistemology refers to the nature of knowledge. The positivist philosophy in social science
adopts the same philosophy of the natural science. It involves objective data collection to be used
in hypotheses testing. Positivism has been applied in business and management research and it
controls mainly the quantitative research. On the other side, the interpretivists believe that
subjectivist ontology cannot separate the researcher from the reality. As the life experience of
the observer cannot be separated from the perceived reality as it the way of making sense in
social life. Linking the research philosophy to the research method and approach is essential as
the researcher has to choose the research approach according to the philosophy he conducts.
Theories describe the relations between concepts, they are universal, but hypotheses describe the
relations between variables. The quantitative approach uses the numerical data and statistical
methods to get the research results. On the other hand, the qualitative research method is used in
interpreting the social interactions. The collected data in non-numerical as it could take the form
of text, image or videos. There also exists a combined way between the quantitative and the
qualitative methods. Mixing between the two methods could create a value added to the research.
Data analysis requires testing the quality and validity of data, including, treatment of missing and
extreme values. Detecting errors is easy to be done through visualization. The qualitative method
of analysis has benefits represented in its ability to provide a detailed analysis of the research

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results through the description of the interrelationships between information processing
performances. On the other side, the quantitative approach has many advantages represented in
the ability to generalize its results to the population or a subgroup of it as it depends on large
samples in most of the cases.

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