Chapter Seven: Characteristics of Quantitative and Qualitative Research Assignment Part I Watch the video by researcher John Creswell to gain a better understanding of a qualitative research method. N
What’s the difference between qualitative and quantitative research? By Saul McLeod, updated 2019 There exists a fundamental distinction between two types of data: Quantitative data is information about quantities, and therefore numbers , and qualitative data is descriptive, and regards phenomenon which can be obs erved but not measured, such as language. Qualitative Research Qualitative research is empirical research where the data are not in the form of numbers (Punch, 1998, p. 4). Qualitative research is multimethod in focus, involving an interpretive, naturalistic approach to its subject matter. This means that qualitative researchers study things in their natural settings, attempting to make sense of, or interpret, pheno mena in terms of the meanings people bring to them. — Denzin and Lincoln (1994, p. 2) An interest in qualitative data came about as the result of the dissatis faction of some psychologists (e.g., Carl Rogers) with the scientific study of psychologists such as the behaviourists (e.g., Skinner ). Since psychologists study people, the traditional approach to science is not seen as an appropriate way of carrying out research, since it fails to capture the totality of human experience and the essence of what it is to be human. Exploring the experience of participants is known as a phenomenological approach (re: Humanism). The aim of qualitative research is to understand the social reality of i ndividuals, groups and cultures as nearly as possible as its participants feel it or live it. T hus, people and groups, are studied in their natural setting. Research following a qualitative approach is exploratory and seeks to ex plain ‘how’ and ‘why’ a particular phenomenon, or behaviour, operates as it does in a particul ar context. Methods (used to obtain qualitative data) Qualitative researchers use a variety of methods to develop deep underst andings of how people perceive their social realities and in consequence, how they act within the social world. For example, diary accounts, open-ended questionnaires, documents, participant observation, and ethnography. The researcher has several methods for collecting empirical materials, r anging from the interview to direct observation, to the analysis of artifacts, docum ents, and cultural records, to the use of visual materials or personal experience. — Denzin and Lincoln (1994, p. 14) A good example of a qualitative research method would be unstructured interviews which generate qualitative data through the use of open questions. This allows the respondent to talk in some depth, choosing their own words. This helps the researcher develop a real sense of a person’s understanding of a situation. Notice that qualitative data could be much more than just words or text. Photographs, videos, sound recordings and so on, can be considered qualitative data. Data Analysis Qualitative research is endlessly creative and interpretive. The researc her does not just leave the field with mountains of empirical data and then easily write up his or her findings. Qualitative interpretations are constructed, and various techniques can be used to make sense of the data, such as content analysis, grounded theory (Glaser & Strauss, 1967), thematic analysis (Braun & Clarke, 2006) or discourse analysis. Key Features Events can be understood adequately only if they are seen in context. Th erefore, a qualitative researcher immerses her/himself in the field, in natural sur roundings. The contexts of inquiry are not contrived; they are natural. Nothing is pred efined or taken for granted. Qualitative researchers want those who are studied to speak for themselv es, to provide their perspectives in words and other actions. Therefore, qualitative re search is an interactive process in which the persons studied teach the researcher ab out their lives. The qualitative researcher is an integral part of the data, without the active participation of the researcher, no data exists. The design of the study evolves during the research, and can be adjusted or changed as it progresses. For the qualitative researcher, there is no single reality, it is subjec tive and exist only in reference to the observer. Theory is data driven, and emerges as part of the research process, evol ving from the data as they are collected. Limitations Because of the time and costs involved, qualitative designs do not gener ally draw samples from large-scale data sets. The problem of adequate validity or reliability is a major criticism. Be cause of the subjective nature of qualitative data and its origin in single contexts, it is diff icult to apply conventional standards of reliability and validity. For example, because of the central role played by the researcher in the generation of data, it is not possible to replicate qualitative studies. Also, contexts, situat ions, events, conditions, and interactions cannot be replicated to any extent nor can generalizati ons be made to a wider context than the one studied with any confidence The time required for data collection, analysis and interpretation are l engthy. Analysis of qualitative data is difficult and expert knowledge of an area is necessa ry to try to interpret qualitative data, and great care must be taken when doing so, for exampl e, if looking for symptoms of mental illness. Strengths Because of close researcher involvement, the researcher gains an insider ‘s view of the field. This allows the researcher to find issues that are often missed (such a s subtleties and complexities) by the scientific, more positivistic inquiries. Qualitative descriptions can play the important role of suggesting possi ble relationships, causes, effects and dynamic processes. Qualitative analysis allows for ambiguities/contradictions in the data, which are a reflection of social reality (Denscombe, 2010). Qualitative research uses a descriptive, narrative style; this research might be of particular benefit to the practitioner as she or he could turn to qualitative repor ts in order to examine forms of knowledge that might otherwise be unavailable, thereby gaining new insight. QuantitativeResearch Quantitative research gathers data in a numerical form which can be put into categories, or in rank order, or measured in units of measurement. This type of data can be used to construct graphs and tables of raw data. Quantitative researchers aim to establish general laws of behaviour and phenonomon across different settings/contexts. Research is used to test a theory and ultim ately support or reject it. Methods (used to obtain quantitative data) Experiments typically yield quantitative data, as they are concerned with measuring things. However, other research methods, such as controlled observations and questionnaires can produce both quantitative information. For example, a rating scale or closed questions on a questionnaire would generate quantitative data as these produce either numerical data or data that ca n be put into categories (e.g., “yes,” “no” answers). Experimental methods limit the possible ways in which a research partici pant can react to and express appropriate social behaviour. Findings are therefore likely to be context-bound and simply a reflectio n of the assumptions which the researcher brings to the investigation. Data Analysis Statistics help us turn quantitative data into useful information to hel p with decision making. We can use statistics to summarise our data, describing patterns, relati onships, and connections. Statistics can be descriptive or inferential. Descriptive statistics help us to summarise our data whereas inferential statistics are used to identify statistically significant differences between groups of data (such as intervention and control groups in a randomised control study). Key Features Quantitative researchers try to control extraneous variables by conducti ng their studies in the lab. The research aims for objectivity (i.e., without bias), and is separat ed from the data. The design of the study is determined before it begins. For the quantitative researcher reality is objective and exist separatel y to the researcher, and is capable of being seen by anyone. Research is used to test a theory and ultimately support or reject it. Limitations Context: Quantitative experiments do not take place in natural settings. In addition, they do not allow participants to explain their choices or the meaning of the qu estions may have for those participants (Carr, 1994). Researcher expertise: Poor knowledge of the application of statistical a nalysis may negatively affect analysis and subsequent interpretation (Black, 1999) . Variability of data quantity: Large sample sizes are needed for more acc urate analysis. Small scale quantitative studies may be less reliable because of the low quant ity of data (Denscombe, 2010). This also affects the ability to generalize study f indings to wider populations. Confirmation bias: The researcher might miss observing phenomena because of focus on theory or hypothesis testing rather than on the theory of hypothesis gen eration. Strengths Scientific objectivity: Quantitative data can be interpreted with statis tical analysis, and since statistics are based on the principles of mathematics, the quantitative approach is viewed as scientifically objective, and rational (Carr, 1994; Denscombe, 2010). Useful for testing and validating already constructed theories. Rapid analysis: Sophisticated software removes much of the need for prol onged data analysis, especially with large volumes of data involved (Antonius, 200 3). Replication: Quantitative data is based on measured values and can be ch ecked by others because numerical data is less open to ambiguities of interpretation. Hypotheses can also be tested because of the used of statistical analysi s (Antonius, 2003). APA Style References Antonius, R. (2003). Interpreting quantitative data with SPSS . Sage. Black, T. R. (1999). Doing quantitative research in the social sciences: An integrated approach to research design, measurement and statistics . Sage. Braun, V. & Clarke, V. (2006). Using thematic analysis in psychology . Qualitative Research in Psychology , 3, 77–101. Carr, L. T. (1994). The strengths and weaknesses of quantitative and qualitative research : what method for nursing?. Journal of advanced nursing, 20(4) , 716-721. Denscombe, M. (2010). The Good Research Guide: for small-scale social research. McGraw Hill. Denzin, N., & Lincoln. Y. (1994). Handbook of Qualitative Research. Thousand Oaks, CA, US: Sage Publications Inc. Glaser, B. G., Strauss, A. L., & Strutzel, E. (1968). The discovery of grounded theory; strategies for qualitative research. Nursing research, 17(4), 364. Minichiello, V. (1990). In-Depth Interviewing: Researching People. Longman Cheshire. Punch, K. (1998). Introduction to Social Research: Quantitatie and Qualitative Approaches. London: Sage Further Information Research Data How to reference this article: McLeod, S. A. (2019, July 30). Qualitative vs. quantitative research. Simply psychology: https://www.simplypsychology.org/qualitative-quantitative.html Designing qualitative research Methods of data collection and analysis Introduction to quantitative and qualitative research Content Analysis Grounded Theory Thematic Analysis