Thank you for your answers.

While Ferrier introduced epistemology; Husserl, Heidegger & Sartre imposed the question of being and phenomenology; Jackson coined transfactualism, and Popper’s stance between the two Extremes; the major question of methods relativity is still debated.

What characteristics distinguish and then, determine the tendency of subjectivity or the objectivity of the research methods?

Since the mid-800, the two ways of understanding reality, positivism and interpretativismo, survive, with ups and downs, within the social sciences along two parallel tracks and contending in each field of investigation. What, at least until the 90s, survived was the idea of the profound diversity - and then distinctness - of the two approaches and, in some cases, their incommensurability.

On this basis there are two lines of research, each corresponding to a particular paradigm, the quantitative approach (positivism) and the qualitative approach (interpretativismo)

I think that in most cases mixed models would be the best way for learning... I will send a nice slide I got about this subject ... 

I think it is smarter to use and combine both methods. They complement each other.

:-)

Dear Alireza,

Qualitative analysis is a complete and detailed description. Quantitative analysis classifies features and counts them to explain what is observed. Its findings can be generalized to a larger population!

Thank you for your answers.

While Ferrier introduced epistemology; Husserl, Heidegger & Sartre imposed the question of being and phenomenology; Jackson coined transfactualism, and Popper’s stance between the two Extremes; the major question of methods relativity is still debated.

What characteristics distinguish and then, determine the tendency of subjectivity or the objectivity of the research methods?

Q & Q SPECTRUM: Although the two: qualitative and quantitative, are differentiable---they are almost inseparable. A purely "quantitative" research would be purely theoretical and serves the purpose of theoretical and empirical treatment, but lack the human side (application to human lives, events, or activities, i.e. social applications). A purely "qualitative" work would almost be "too human" lacking the numerical and theoretical aspects that are familiarly expected among our peers. A mixed method would seem to satisfy both ends of the spectrum, but a research done aiming to please the audience would lessen its claim for empirical supremacy and scientific objectivity.

BACK TO BASICS: We have to return to the basic question of the research: issues, purpose, objective and intended contribution. The issue of qualitative or quantitative becomes a matter of methodology. Does the elected methodology answer the research question? Does it meet scientific standard, i.e. standard currently accepted in our peer community?

RESEARCH DOCTRINE: All researchers had been educated and trained by the institutions from which they came, i.e. undergraduate, graduate or post-graduate studies. Through this long journey all of us had been influenced by the research doctrine under which we have been trained. Fruits do not generally fall far from the tree that produced them. Once in a while we will see researchers that would break away from the "template" and do something innovative---although rare, those are the ones that push the frontier in research. Consider how Stephen Hawking describe blackhole and compare it to the description given by Albert Einstein. Both are at the opposite poles in theoretical framework describing the same event, yet both are equally "sound." As long as the research meets scientific objectivity and whose claims for empiricism could be independently verified, it could be either qualitative or quantitative.

Purpose of the both methods are the same but procedure of data collection is different. In quantitative methods, we gather bigger data and analyze by applying N-number of statistical  tools. Whereas in qualitative methods, we gather smaller data and make foundation for quantitative methods. Opposite may also be used.

I think 'qualitative' analysis mainly deals with descriptions, while 'quantitative' deals with numbers.

Qualitative deals with descriptions & quantitative deals with numbers. Assume that you placed the palm of your hand on the head front of your child & then judged that s/he is warmer than usual. You may describe this case as fever “qualitative description”. Bring a thermometer & measure his/her temperature and you may find it to be 37.5 oC ; you will phone MD and give “quantitative description” & you will be told that the case is not medically considered as fever but if it is 38.5 oC, then there has to be fast remedial action. Many times, you will hear high caliber scholars calling for “FACTS & FIGURES”. In social & behavioral sciences, collecting qualitative data is fine but more reliability & validity are gained upon adding quantitative data to them . Example: Country (X) may be described as “rich” but it may just contain one rich ruling family, so it is more pertinent to give the number of the rich persons in that country (may be the rich are 800 while the poor are 8 million, so the country is largely poor).

Dear Alireza;

Wonderful discussion so far.  Perhaps the issue here is---methodology Vs Method! Moreover, the intellectual integrity, trustworthiness and diversity of consumer scholarship depend on researchers accounting for the methodological (philosophical) underpinnings of their work---not just the methods used to sample, collect and analyze data and report the results ! Please take a look at the following research study---you may find it helpful with your current research question(s):

In this study, McGregor and Murane (2010) argued that many scholars do not clearly differentiate between methodology and method. To address this issue, the authors distinguish between these two concepts, identifies four axioms of methodologies, identifies and describes two overarching research paradigms (positivism and post-positivism), contrasts quantitative/qualitative with positivistic/post-positivistic, and positions consumer scholarship with three dominant research methodologies: scientific, interpretive and critical!

Furthermore the authors argue that---regardless of the research paradigm or methodology, a more pressing question is not what kind of science (natural, human or social) but whether or not the scholarship is good science! Does the work make an intellectual contribution that can be trusted? A key to answering this question is people’s familiarity with the nuances of research paradigms and methodologies. This conversancy contributes to the integrity of consumer scholarship, enables users to trust the resultant body of knowledge and increases opportunities to create a more diverse body of consumer studies knowledge. In other words, methodological accountability is a responsible, timely, professional posture for consumer scholars.

• McGregor, S. T., & Murnane, J. A. (2010). Paradigm, methodology and method: intellectual integrity in consumer scholarship. International Journal Of Consumer Studies, 34(4), 419-427.

Hope this helps!

Nadeem

Dear @Alireza, there were some very good threads regarding the issue of quantitative vs qualitative, many answers and opinions about. I have attached the links to threads. Hope it will be good for research!

https://www.researchgate.net/post/What_methodology_do_you_prefer_Qualitative_or_Quantitative_Why

https://www.researchgate.net/post/Which_type_of_research_do_you_prefer_to_conduct_Quantitative_or_Qualitative

https://www.researchgate.net/post/When_quantitative_and_qualitative_results_does_not_match_and_is_contradictory_what_to_do_in_a_mix_method_research_design

Lots of good discussion here, but just want to make the case that quantitative does not equal positivism (at least not necessarily). See the below illustrating and calling for a non-positivist, critical realist quantitative social science

https://www.researchgate.net/publication/256801634_The_practice_of_quantitative_methods

Chapter The practice of quantitative methods

One of the central issues when it comes to discussions of epistemology is, perhaps ironically, confusion over various terms from the definition of positivism to the relationship between methodology and epistemology. For one thing, I don’t think many people (if any) would find much agreement with Comte’s elucidation of positivist epistemology, despite the fact that he coined the term. Nor is post-positivism so neatly dichotomized; Harding’s Is Science Multicultural: Postcolonialisms, Feminisms, and Epistemologies explores in great detail various 20th century and modern epistemologies that are anything but positivist, yet no attention is given to either positivism or post-positivism (still less to quantitative vs. qualitative). Zammito’s A nice Derangement of Epistemes: Post-Positivism in the Study of Science from Quine to Latour is devoted to the shift from the positivism which developed out of Comte’s work and perhaps even more importantly the Vienna Circle. Yet here again no mention is made of either qualitative or quantitative epistemologies. Part of this is elucidated in the paper “The Debate about Quantitative and Qualitative Research: A Question of Method or Epistemology” (The British Journal of Sociology 35(1); 1984). Much of the quantitative vs. qualitative debate is integrally and intricately tied to methodologies, whereas theories of epistemic justification, externalism vs. internalism, etc., are more “purely” philosophical.

In fact, while it is quite true that many have devoted much work to the quantitative vs. qualitative debate, a great many have (for many years now) submitted a sizable number of proposals, criticisms, and even pleading exhortations that all suggest the dichotomy to be largely or wholly contrived. The positivism of the 19th century, itself in many ways a development in the tradition of Laplacian determinism and the successes of physics, suddenly found itself besieged on several fronts during the early and mid-twentieth century. It is rather extraordinary how precisely we can see the tides turn. Max Planck’s advisor warned him not to go into physics because there was basically nothing left to discover. In his (in)famous statement concerning the two clouds Lord Kelvin referred to what he and others thought to be the last questions before we would be done with physics and scientists would have to examine phenomena higher in the scientific “hierarchy”. Hilbert’s famous address concerning which problems were most important for mathematicians to solve in the new century (the 20th) not only reflected a positivist epistemology but an almost quintessential logical positivism (motivated by the successes of Frege, Boole, and later believed to be realized by the work of Russell & Whitehead).

Then came the attacks. The first was the realization that the trivial unsolved problems in physics rang the death knell for physics as it was understood (hence the qualifier “classical” in classical physics). The problem wasn’t simply that it turned out there was far more left to discover. It was the realization that the debate over whether light was a wave of composed of parts, a central component to the entirety of physics even before Newton’s corpuscular theory, was flawed. Experiments from Young onwards had most certainly “proved” that light was a wave, only for Einstein to “prove” that it wasn’t. No other example so drove home how tightly hypotheses are wound with the theories that they seek to confirm: the generation of hypotheses, the manner in which they are tested, and the interpretation of the results are all theory-laden.

Next came Turing, whose foundational work in computability theory too often overshadows just how problematic his work was seen to be at the time. Turing solved part of the problems that Hilbert had declared most important by showing that they couldn’t be solved. Not long after, Gödel completely eradicated the heart of logical positivism. To axiomize all of mathematics by way of a logical calculus had been a goal of mathematicians since Leibniz (although he never published his work on symbolic logic, and by the time it was known Frege had independently discovered/invented it). Gödel proved this could not ever happen, and the “queen of the sciences”, mathematics, was suddenly relegated by most to a tool for scientists or a separate discipline.

After years of debate among those like Putnam, Quine, Popper, and others who were either trying to re-establish a remnant or remade positivism or show that this was impossible, there emerged a fresh challenge to any hope of purely quantitative scientific epistemology (whether the logical framework of Popper or the counterfactual approach of Lewis or the probabilistic framework of Jeffreys). The work by Kuhn was not only groundbreaking (and deeply troubling) but for the most part quite novel. However, as Rheinberger describes in Historische Epistemologie, Kuhn was hardly the only historian, scientist, or philosopher to point to the “troubling history” (to borrow from Conant) of scientific discovery (nor was he the most radical).

There is something seductive, it seems, in the inclusion of mathematical formulae and formal logic into one’s work. Many historians, for example, have attempted to ground their discipline not only in logic but also Bayesian inference/reasoning. Qualitative analyses are often given short shrift compared to the application of quantitative methods that yield garbage. Worse still is the quantitative approach to qualitative inquiry which abounds across many sciences. Apart from the neat, crisp, and unambiguous nature of a numerical result (no matter how ill-founded), qualitative methods at times are so ambiguous that it is difficult even to describe how they work (modern ethnology is perhaps the best exemplar).

However, just as behaviorism’s justification for its approach died (i.e., that the “mind” is a black box that cannot be observed and thus is beyond the scope of science), so too has the logical positivism (and positivism in general), at least in its “classic” forms. The debate between quantitative vs. qualitative is largely one of methods, and as qualitative approaches often involve quantitative methods, even this methodological distinction is often a mischaracterization.

In short, there is no straightforward dichotomy between the two epistemologies, as they aren’t really two but multitudes that overlap.

Quantitative, qualitative and mixed research in social sciences

The quantitative tradition is based on a belief that the study of society is no different than the scientific study of any other element of our world. It premises scientific method, hypothesis testing, deductive logic, objectivity and quantification.

The qualitative tradition critiques quantitative assumptions and premises inductive logic, subjectivity, multiple truths, the political nature of research, and the value of depth over quantity. Qualitative research strategies for achieving credibility include thoroughness, i.e. saturation, crystallization, prolonged engagement, persistent observation, broad representation and peer review, and confirmation, i.e. triangulation, member checking, and full explication of method.

“Mixed” studies traverse traditional divides and can help you capitalize on the best of both traditions while overcoming their shortcomings. “Mixed” approaches can be premised in the quantitative tradition with acceptance of qualitative data; the qualitative tradition with acceptance of quantitative data; or be driven by the questions themselves.

source: Zina O’Leary (2009) The Essential Guide to Doing Your Research Project. London: Sage

Quantitative and qualitative research

• Quantitative research focuses on numbers
• Quantitative research is best if you want to generalize to a larger population (find trends, patterns . . . )
• Qualitative research focuses on text. Text is what people say (verbally or in written form)
• Qualitative research is best if one wants to study a particular subject in depth
• Both quantitative and qualitative research are useful and needed in research in business and management. Both are important and both can be rigorous

The discrimination of quality versus quantity belongs epistemologically to the aristotelian categories. These are not thought to be aspects of the reality but rather aspects of the mind (see also Kant). Therefor it is an epistemological problem to define a research methodology as quantitative or qualitative.

In social science quantitative research often is thought to prefer mathematics whereas qualitative research prefers language. But the problem in this interpretation is that language often uses quantitative terms (e.g. much, often, one, rare, many, seldom) and mathematical formulas (e.g. statistical models) are qualities. In consequence it is not possible for language or mathematics to avoid the use of quantitative or qualitative concepts.

Historically the concept of qualitative research came up as a methodology critical movement, which primarily criticized number fetishism. Supporters wanted to implement alternative values like meaning and demanded alternative approaches like better descriptions and interpretations. Some of these critical considerations are really relevant but do not lead to a episetmologically justified distinction of quantitative methodology versus qualitative methodology.

Research should not be limited by perspective. Methods should be used adequate respecting the phenomenon of interest.

Regards

You may have heard the world is made up of atoms and molecules, but it's really made up of stories. When you sit with an individual that's been here, you can give quantitative data a qualitative overlay.

William Turner

The primary aim of a Qualitative Research is to provide a complete, detailed description of the research topic. It is usually more exploratory in nature. Quantitative Research on the other hand focuses more in counting and classifying features and constructing statistical models and figures to explain what is observed.

The main distinguishing feature is the approach one selects to walk along.

I must appreciate your idea of throwing this question. It is really an interesting one.

Nice slide about this issue.

I think that working on integrate both research methods as complementary would be the way.

Regards to all. 

The main function of qualitative research is to provide meaningful quantification of empirical content, whenever it is possible.

"If there were only one truth, you couldn’t paint a hundred canvases on the same theme." Pablo Picasso

Quantitative vs. Qualitative is the classic left vs. right brain clash. But instead of picking a side in research, why not use both? "Enter Qualitative Research or the prototypical right side of your brain. Qualitative research often gets a bad rap for being creative-heavy and scientific-light. Therefore it goes over-looked and is viewed as too expensive for its return.... it is still appropriate to cut out qualitative research and go directly to quantitative. In what instances is that true? A situation like a tracker study where the first wave of the survey has already been designed and you are looking to benchmark data, government standardized surveys where wording and answer choices cannot be customized, or situations where hard data is needed almost immediately with no wiggle room on budget or timeframe."

https://rmsbunkerblog.wordpress.com/tag/quantitative-research/

http://citiesheart.com/2014/06/minutes-for-discussion-of-qualitative-and-quantitative-research-in-urban-studies/