[Social Science Research Methods] Quantitative vs. Qualitative Research: Key Characteristics and Differences

How should we study human beings and society in the social sciences?

Researchers can measure people's behavior numerically and analyze it statistically. Alternatively, they can meet people directly, listen to their stories, and explore their thoughts and experiences in depth.

These different approaches have led to the development of two major research traditions in the social sciences: quantitative research and qualitative research.

Quantitative research seeks to objectively analyze social phenomena using measurable numerical data and statistical methods, whereas qualitative research aims to gain an in-depth understanding of the subjective meanings, experiences, and social contexts underlying human behavior.

The differences between these two approaches go beyond how data are collected. They also reflect different philosophical perspectives on how human beings and society should be understood and studied.

1. What Is Quantitative Research?

Quantitative research is an approach based on the idea that social and cultural phenomena can be systematically measured and quantified, and that statistical analysis can be used to identify patterns and relationships within social phenomena (Bryman, 2016; Creswell & Creswell, 2018).

Simply put, quantitative research involves converting social phenomena into numerical data and analyzing them statistically.

For example, consider the following research question:

“Does increased smartphone use lead to lower academic performance among adolescents?”

A researcher could survey 1,000 adolescents about their average daily smartphone use and academic performance and then statistically analyze the relationship between these two variables.

# Key Characteristics of Quantitative Research

① Methodological Monism

Methodological monism does not necessarily mean that natural and social phenomena are completely identical. Rather, it refers to the view that scientific methods developed in the natural sciences—such as observation, measurement, and hypothesis testing—can also be applied to the study of social phenomena.

From this perspective, researchers can identify certain patterns and relationships in social phenomena through systematic measurement and analysis.

② Identifying General Relationships and Patterns

Quantitative research places considerable emphasis on analyzing relationships between variables and identifying social patterns that repeatedly occur under certain conditions.

For example, researchers can statistically examine the relationship between income and educational attainment, education and health, or unemployment and crime.

When supported by an appropriate research design, quantitative research can also be used to examine causal relationships between variables.

③ A Deductive Approach to Research

Quantitative research typically follows the process of theory → hypothesis → data collection → analysis → hypothesis testing (Bryman, 2016).

Researchers derive a research question or problem from an existing theory, formulate a hypothesis, and then use empirical data to test whether the hypothesis is supported.

However, not all quantitative research is necessarily deductive. Inductive approaches may also be used in exploratory data analysis or quantitative studies designed to identify new patterns in the data.

④ Operational Definition of Concepts

In quantitative research, it is important to transform abstract social concepts into variables that can actually be measured.

This process is known as an operational definition.

For example, an abstract concept such as “socioeconomic status” cannot be directly entered into a statistical analysis. Instead, it can be measured using specific variables such as income, educational attainment, occupation, and assets.

Similarly, concepts such as depression or life satisfaction can be quantified using multiple survey questions or standardized scales.

These characteristics of quantitative research can also be seen in my study, “Longitudinal Effects of Life Satisfaction on Smoking Status of Korean Adult Men.”

In this study, I used 12 years of longitudinal data from the Korea Welfare Panel Study and applied the Cox proportional hazards model, a survival analysis method used to examine the risk of an event occurring over time, to investigate the relationship between life satisfaction and smoking behavior among adult men.

To operationalize the abstract concept of life satisfaction, eight satisfaction variables were used as independent variables: satisfaction with leisure activities, social relationships, family relationships, health, occupation, household income, residential environment, and overall life satisfaction.

Each satisfaction variable was classified into three categories according to the respondent’s level of satisfaction: Not satisfied, Moderately satisfied, and Satisfied. These categories were then coded numerically—for example, as 1, 2, and 3—so that they could be used in statistical analysis.

In other words, rather than making an abstract judgment such as, “Is this person satisfied with his life?”, the study broke down the concept of life satisfaction into several specific domains of everyday life. Satisfaction within each domain was then categorized according to predefined criteria and coded numerically to create variables suitable for statistical analysis.

Thus, quantitative research often follows the process of:

Abstract concept → Specific measurement items → Numerical or categorical measurement and coding → Statistical analysis

This study was published in the Journal of Preventive Medicine and Public Health in 2025.

https://doi.org/10.3961/jpmph.24.664

⑤ Common Data Collection Methods

Quantitative research commonly uses the following methods:

- Questionnaires and surveys

- Experiments

- Structured observation

- Analysis of administrative statistics and existing statistical data

- Analysis of large-scale panel and survey data

In contemporary social science research, quantitative researchers use a wide variety of data sources beyond traditional surveys, including government statistics, population censuses, panel data, healthcare data, administrative records, and big data.

2. What Is Qualitative Research?

Qualitative research is based on the view that human behavior cannot be fully understood simply through numbers or statistical relationships between variables.

This is because people interpret the social situations in which they live, assign meaning to their experiences, and act based on those interpretations.

Therefore, qualitative research places particular emphasis on gaining an in-depth understanding of what people experience and how they perceive, interpret, and make sense of those experiences.

For example, consider the following research question:

“What kinds of alienation and anxiety do adolescents who are highly dependent on smartphones experience in their everyday lives?”

To investigate this question, a researcher might meet directly with adolescents and conduct lengthy, in-depth interviews.

Rather than simply measuring anxiety on a scale from 1 to 10, the researcher might ask questions such as:

“When do you feel anxious?”

“What does the smartphone mean to you in your relationships with friends?”

“How do you feel when you cannot use your smartphone?”

Through these types of questions, the researcher can explore participants’ experiences, interpretations, and the meanings they attach to smartphone use in much greater depth.

# Key Characteristics of Qualitative Research

① Methodological Dualism

Methodological dualism is based on the view that social phenomena created by human beings differ fundamentally from natural phenomena and therefore cannot be fully studied using the same methods as the natural sciences alone.

When a stone falls to the ground, the stone has no intentions, values, or beliefs of its own.

Human actions, however, are different. Decisions such as quitting a job, getting married, or migrating to another country involve various meanings shaped by personal values, experiences, emotions, and social relationships.

Therefore, to understand human behavior, researchers must also examine the meanings that individuals attach to their own actions.

② In-Depth Understanding

One of the major goals of qualitative research is to gain an in-depth understanding of the social realities experienced by research participants.

Rather than focusing only on questions such as “How many people engage in this behavior?”, qualitative researchers also emphasize questions such as:

“Why do people behave this way?”

“What does this behavior mean to them?”

“In what kind of social environment does this behavior occur?”

These questions allow researchers to explore not only what people do, but also how they understand and interpret their experiences.

③ An Inductive Approach to Research

Qualitative research generally emphasizes a process such as:

Fieldwork and data → Identification of recurring patterns → Development of concepts and categories → Interpretation or theory development (Creswell & Creswell, 2018).

Rather than beginning with a rigid hypothesis and testing it against empirical data, qualitative researchers often observe people's experiences, narratives, and behaviors and gradually identify important meanings and recurring patterns.

However, qualitative research is not always purely inductive. Many qualitative studies also draw on existing theories and theoretical frameworks to guide the interpretation of data.

④ The Importance of Social Context

Qualitative research generally assumes that human behavior cannot be fully understood when separated from the social and cultural environments in which people live.

The same behavior may have different meanings depending on the historical period, society, culture, social class, organization, or other social contexts in which it occurs.

For this reason, qualitative researchers pay close attention to the environments in which people actually live and to the social relationships surrounding their experiences and behavior.

⑤ Common Data Collection Methods

Qualitative research commonly uses the following methods:

- In-depth interviews

- Participant observation

- Non-participant observation

- Focus group interviews (FGIs)

- Life history research

- Textual analysis of diaries, letters, documents, and other materials

- Ethnographic research

Among these methods, in-depth interviews, which allow participants to describe their experiences in their own words, and participant observation, in which researchers enter a social setting and observe people's behavior and culture directly, are particularly representative methods of qualitative research.

⑥ A Limitation of Qualitative Research: Difficulty of Generalization

Qualitative research generally collects in-depth information from a relatively small number of participants. As a result, it is often more difficult to obtain a statistically representative sample than in quantitative research.

In particular, qualitative studies frequently rely on purposive sampling, in which researchers deliberately select individuals who are particularly relevant to the research question or who have specific experiences, rather than probability sampling, in which participants are randomly selected from a target population.

Therefore, it is difficult to statistically generalize the experiences, meanings, or behavioral patterns identified within a particular group to an entire population.

For example, even if a researcher conducts in-depth interviews with 10 North Korean defectors to examine their experiences of settling into South Korean society, the findings cannot necessarily be interpreted as representative of the experiences of all North Korean defectors.

However, the primary purpose of qualitative research is generally not to statistically generalize findings to an entire population. Rather, it is to develop a deeper understanding of particular social phenomena and of the experiences, meanings, and contexts of specific groups.

Therefore, the difficulty of statistical generalization should be understood in relation to the broader goals and purposes of qualitative research.

4. Quantitative vs. Qualitative Research: Key Differences

The key differences between quantitative and qualitative research can be summarized as follows.

# Quantitative Research

Quantitative research is commonly associated with positivism and methodological monism. Its main goal is to identify relationships and recurring patterns in social phenomena and, when appropriate, to generalize findings to a broader population or make predictions.

It typically follows a deductive approach and relies primarily on numerical and statistical data. Common data collection methods include surveys, experiments, and the analysis of existing statistical or administrative data.

Quantitative research is particularly suitable for relatively large samples, and statistical methods are used to analyze relationships between variables. Researchers generally emphasize objectivity, measurement, standardization, and replicability.

One of its major strengths is that it allows researchers to systematically compare groups, examine relationships between variables, and, when appropriate sampling and research designs are used, generalize findings to a larger population.

However, reducing complex social phenomena to measurable variables may sometimes make it difficult to fully capture the meanings, experiences, and social contexts underlying human behavior.

# Qualitative Research

Qualitative research is commonly associated with intellectual traditions such as interpretivism and phenomenology and is often linked to methodological dualism.

Its primary goal is to develop an in-depth understanding of people's meanings, experiences, behaviors, and social contexts.

Qualitative research often follows an inductive approach and works primarily with non-numerical forms of data, including language, behavior, personal experiences, interviews, observations, and documents.

Common data collection methods include in-depth interviews, participant observation, focus group interviews, and document analysis. Qualitative studies generally focus on relatively small numbers of participants or cases so that researchers can examine them in greater depth.

Data are commonly analyzed through coding, categorization, thematic analysis, and content analysis. Rather than focusing primarily on standardization, qualitative researchers emphasize understanding participants and their experiences within their particular social and cultural contexts.

The major strength of qualitative research is its ability to explore complex human experiences and meanings in considerable depth.

However, because qualitative studies often involve relatively small and purposively selected samples, their findings may have limited statistical generalizability to a broader population.

5. The Same Social Phenomenon Can Be Studied in Completely Different Ways

The differences between quantitative and qualitative research become much easier to understand when we consider how the same social phenomenon can be studied using these two approaches.

For example, suppose we want to study smartphone use among adolescents.

(1) Quantitative Research

# Research Question

“Does increased smartphone use lead to lower academic performance among adolescents?”

# Research Method

A researcher surveys 1,000 adolescents and measures their average daily smartphone use and academic performance.

The researcher then uses statistical methods, such as regression analysis, to examine the relationship between these two variables.

The key questions are: How much time do adolescents spend using smartphones? How much does academic performance vary with smartphone use? Is there a statistically significant relationship between the two variables?

(2) Qualitative Research

# Research Question

“What kinds of experiences do adolescents who use smartphones excessively have in their daily lives and peer relationships?”

# Research Method

A researcher conducts in-depth interviews with adolescents to explore their experiences with smartphone use, relationships with friends, conflicts with family members, feelings of anxiety, and experiences of alienation.

The key is to understand how adolescents perceive their own smartphone use and what meanings they attach to their experiences.

Thus, even though both approaches examine the same phenomenon—smartphone use—the research questions, types of data, and research methods can be completely different.

6. Why Did Quantitative Research Emerge? — The Success of the Natural Sciences and Positivism

To understand the historical background of quantitative research, it is necessary to examine the Scientific Revolution and the development of the natural sciences in early modern Europe.

During the Scientific Revolution of the 17th century, scientists such as Galileo Galilei and Isaac Newton demonstrated that natural phenomena could be systematically observed, measured, and explained through general laws.

The success of Newtonian mechanics, in particular, strengthened the belief that the natural world operates according to discoverable laws and that human reason and systematic observation can uncover those laws.

Through the Enlightenment of the 18th century and into the 19th century, this way of thinking increasingly influenced attempts to study human society as well.

“If laws exist in nature, might there also be certain laws governing human society?”

One of the most influential thinkers to develop this perspective was the French philosopher Auguste Comte (1798–1857).

Comte argued that social phenomena could also be studied scientifically through observation and comparison, and his work had an important influence on the development of the positivist tradition of studying society scientifically (Comte, 1853).

The positivism he developed emphasized knowledge that could be established through observation and experience and sought to establish sociology as a scientific discipline.

Within this intellectual tradition, a research approach gradually developed that emphasized the systematic measurement of social phenomena, the collection of empirical data, and the identification of general patterns and regularities.

7. Why Did Qualitative Research Emerge? — Human Beings Are Different from Objects in Nature

As attempts to apply the methods of the natural sciences to the social sciences developed, however, criticisms of this approach also emerged.

The central question was simple:

Can human behavior really be explained in the same way as natural phenomena?

The German philosopher Wilhelm Dilthey (1833–1911) argued that the natural sciences and the disciplines concerned with human beings differ in their fundamental character.

In the natural sciences, the primary goal is to explain (Erklären) the causes and laws underlying natural phenomena. To study human history and society, however, Dilthey argued that researchers must also seek to understand (Verstehen) the meanings that people attach to their actions and experiences (Dilthey, 1883/1989).

This intellectual perspective also had an important influence on the sociologist Max Weber (1864–1920).

Weber viewed sociology as a discipline that seeks to interpretively understand human social action and to causally explain its course and consequences (Weber, 1978).

For example, imagine a person who works hard every day from early morning until late at night.

If we simply measure working hours, we can determine how many hours that person works each day.

However, numbers alone cannot fully explain why the person works so hard.

It may be because of economic necessity, a sense of responsibility toward family, religious values, or a strong desire for success.

In other words, to properly understand human behavior, researchers need to examine not only how much or how often people behave in a certain way, but also the meanings and motivations underlying their behavior.

This intellectual tradition later interacted with approaches such as hermeneutics, phenomenology, symbolic interactionism, and ethnographic research, providing an important foundation for the development of modern qualitative research methods.

8. Are Quantitative and Qualitative Research Opposing Approaches?

Historically, there have been considerable philosophical and methodological debates between the quantitative and qualitative research traditions.

In contemporary social science, however, neither approach is generally regarded as absolutely superior to the other. The most appropriate research method depends on the field of study, research question, and purpose of the research.

Depending on the research question and objectives, researchers may also use Mixed Methods Research, which combines the strengths of quantitative and qualitative approaches (Creswell & Creswell, 2018).

For example, researchers might first conduct a survey of 5,000 adolescents nationwide to examine the statistical relationship between smartphone use and depression.

They could then conduct in-depth interviews with a smaller group of adolescents to explore in greater detail why and how smartphone use affects their emotions and social relationships.

While quantitative research can help answer questions such as “How common is this phenomenon?” and “What variables is it associated with?”, qualitative research can provide deeper insight into questions such as “Why does this phenomenon occur?” and “How do people experience it?”

Therefore, quantitative and qualitative research should not be viewed solely as competing approaches. They can also complement each other by addressing the limitations of each method.

Conclusion — Measuring Society Through Numbers, Understanding Society Through Stories

The most fundamental difference between quantitative and qualitative research lies in how they approach social phenomena and the kinds of research questions they seek to answer.

Quantitative research transforms social phenomena into measurable variables and uses large-scale data and statistical analysis to identify relationships and recurring patterns. It is particularly useful for comparing groups, examining relationships between variables, making predictions, and, under appropriate research designs and sampling methods, generalizing findings to broader populations.

Qualitative research, in contrast, enters into the specific social environments in which people live and seeks to develop an in-depth understanding of the meanings, experiences, and contexts underlying their actions and everyday lives.

At the same time, the scope of quantitative research in contemporary social science has expanded considerably compared with the past.

One of the most important reasons for this expansion is the explosive growth in the volume and variety of data available for analysis.

In the past, researchers often had to collect much of their data directly through surveys and other forms of primary data collection. Today, however, social scientists can draw on an enormous range of data sources, including large-scale administrative and demographic data collected by governments and public institutions, longitudinal panel data that follow the same individuals over extended periods, healthcare, education, and labor market data, as well as vast amounts of data generated through the internet and digital technologies (Bryman, 2016).

Advances in computing and statistical analysis have also played an important role in the expansion of quantitative research.

Datasets containing hundreds of thousands or even millions of observations, which would have been extremely difficult to process in the past, can now be analyzed using modern computers and statistical software. In addition to traditional statistical techniques such as regression analysis, social scientists now use a wide range of advanced methods, including multilevel modeling, longitudinal data analysis, spatial statistics, causal inference, and machine learning.

Objective data are particularly important when studying public policy and social problems. Researchers often need to determine how many people are affected, which groups are disproportionately affected, and whether particular policies or institutions actually produce measurable effects.

For example, understanding social issues such as low fertility, population aging, income inequality, unemployment, educational inequality, regional disparities, and health inequalities requires more than an in-depth understanding of individual experiences. Researchers also need to use large-scale data to identify broader patterns and trends occurring across society as a whole.

For this reason, quantitative research using large-scale datasets is widely conducted across contemporary disciplines such as sociology, economics, political science, demography, education, and public health.

More recently, advances in big data, artificial intelligence (AI), and machine learning have further expanded both the types of data that quantitative researchers can analyze and the range of analytical methods available to social scientists.

Moreover, one of the major strengths of quantitative research is that, when it uses large and representative samples, its findings can often be generalized to a broader population.

In particular, large-scale survey datasets based on probability sampling, in which participants are selected from a target population using probability-based sampling procedures, can be designed so that the sample reflects the characteristics of that population. Therefore, compared with qualitative research that examines a relatively small number of cases in depth, quantitative research using such data is generally better suited for statistically generalizing findings to a larger population.

In the United States, for example, large-scale national datasets such as the National Health and Nutrition Examination Survey (NHANES), National Health Interview Survey (NHIS), American Community Survey (ACS), and General Social Survey (GSS) are widely used in social science, demography, economics, and public health research.

These large-scale surveys employ systematic sampling designs intended to represent their respective target populations. When researchers appropriately account for survey weights and complex sampling designs, characteristics observed in the sample can be used to produce estimates for the broader population.

In other words, one of the important strengths of quantitative research is its ability to use large-scale, representative survey data to move beyond phenomena observed among individuals or a small number of cases, identify patterns at the population level, and statistically generalize findings to a broader population.

However, it is difficult to claim that one approach is always more scientific or inherently superior to the other.

Human society is, after all, a world that can be measured through numbers, but at the same time, it is also a world of meanings and experiences that cannot be fully explained by numbers alone.

No matter how much data researchers collect, numbers alone cannot fully reveal how people experience and interpret particular situations or what meanings they attach to their actions. For this reason, qualitative research remains essential in areas where an in-depth understanding of human experience, subjective meaning, and social context is required.

The Most Important Question: What Are You Trying to Study?

Ultimately, the most important consideration is the kind of research question you are trying to answer.

If the goal is to identify general patterns across society or examine relationships between variables, quantitative research may be particularly effective.

In contrast, if the goal is to understand in depth how members of a particular group experience and interpret a social phenomenon, qualitative research may be more appropriate.

Qualitative research can be especially useful when studying minority populations, hard-to-reach groups, and small groups of highly specialized experts.

Quantitative research, particularly survey research, generally requires a sufficiently large sample to statistically analyze group characteristics or relationships between variables. However, obtaining large and representative samples can be difficult when studying populations that are relatively small or difficult to access, such as people with rare diseases, children of incarcerated parents, or undocumented immigrants.

Qualitative research, by contrast, can use in-depth interviews and other methods with a relatively small number of participants to explore their experiences, perceptions, and the meanings they attach to those experiences. It can therefore be particularly valuable for studying the lives and experiences of minority or specialized populations for which obtaining a large sample may be difficult.

Qualitative research also has important advantages when studying groups with highly specialized expertise or rare forms of experience.

For example, studies such as “How Do Five Successful Startup Founders Make Major Business Decisions?” or “How Do CEOs of Global Companies Perceive and Overcome Corporate Crises?” may be better suited to in-depth interviews with a small number of individuals who have actually had these experiences than to a survey involving hundreds of respondents.

The purpose of such research is not to statistically estimate how many people made a particular decision. Rather, it is to explore in depth how experts make judgments and decisions in critical situations, what kinds of knowledge and experience they draw upon, and what forms of practical know-how they have accumulated through those experiences.

Such complex experiences and forms of tacit knowledge may be difficult to capture adequately through numerical measures or standardized survey questions alone.

For example, if the research question is “What is the relationship between smartphone use and academic performance among adolescents?”, and the goal is to identify general patterns, relationships between variables, or the magnitude of an association across a broad adolescent population, a quantitative approach may be appropriate.

In contrast, if the research question is “How do adolescents with disabilities experience smartphone use, and what meanings do they attach to those experiences?” or “How do successful startup founders make decisions during major business crises?”, a qualitative approach may be more appropriate because the goal is to understand the experiences and decision-making processes of particular groups in depth.

Ultimately, research methods should not be selected simply according to a researcher’s personal preference. The most important principle is to choose the method that best fits the research question and research purpose.

Combining the Two Approaches: Mixed Methods Research

Contemporary social scientists also combine quantitative and qualitative approaches to develop a more comprehensive understanding of social phenomena.

Mixed Methods Research combines quantitative and qualitative approaches within a single study or broader research program. The key is not simply to conduct one quantitative study and one qualitative study separately, but to connect and integrate the two types of data and findings so that they jointly provide a more comprehensive answer to the research question.

For example, qualitative research may help explain why a statistical relationship identified through quantitative analysis occurs.

In practice, the two approaches often require substantially different forms of methodological expertise.

Quantitative research requires expertise in areas such as statistical analysis, research design, measurement, and data management, whereas qualitative research requires expertise in areas such as in-depth interviewing, participant observation, coding, thematic analysis, and interpretation.

For this reason, large-scale mixed methods projects sometimes involve research teams in which quantitative and qualitative researchers collaborate, bringing different methodological expertise to the same research problem.

Mixed Methods Research has the advantage of drawing on the strengths of both approaches and can provide a more comprehensive understanding of complex social phenomena. However, it also has disadvantages. Combining quantitative and qualitative methods generally requires more time and resources, while the research design, data collection, analysis, and integration of findings can become considerably more complex.

References

Bryman, A. (2016). Social Research Methods (5th ed.). Oxford University Press.

Comte, A. (1853). The Positive Philosophy of Auguste Comte. John Chapman.

Creswell, J. W., & Creswell, J. D. (2018). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (5th ed.). SAGE Publications.

Denzin, N. K., & Lincoln, Y. S. (Eds.). (2018). The SAGE Handbook of Qualitative Research (5th ed.). SAGE Publications.

Dilthey, W. (1989). Introduction to the Human Sciences. Princeton University Press. (Original work published 1883)

Weber, M. (1978). Economy and Society: An Outline of Interpretive Sociology. University of California Press.

Yin, R. K. (2018). Case Study Research and Applications: Design and Methods (6th ed.). SAGE Publications.