Quantitative Research Method: Positivism Philosophy and Numerical Data Analysis

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 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).

Types of Quantitative Research: Survey, Correlational, Experimental, or Causal-Comparative Research

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 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 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).

Qualitative Research Method: Interpretivism Philosophy and Non-Numerical Data Analysis

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).

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).

Benefits of Combined Research Methods

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 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 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).

Data Analysis Techniques in Quantitative and Qualitative Research

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 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 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.

Thematic Data Analysis in Qualitative Research

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