For the full research must have the skills of quantitative and qualitative analysis. It is also important to qualitative analysis was confirmed by quantitative estimates. Therefore it is necessary to combine qualitative and quantitative methods of analysis. I would not share them.

For the full research must have the skills of quantitative and qualitative analysis. It is also important to qualitative analysis was confirmed by quantitative estimates. Therefore it is necessary to combine qualitative and quantitative methods of analysis. I would not share them.

Research is a qualitative work; therefore, I like to do  qualitative research.

My research fields dictates quantitative research is preferred. Engieers should strive to be precise and rigorous, and therefore qualitative research is not good enough.

Quantitative conclusions, if possible, include qualitative information, and therefore should be aimed for, in my personal view.

Experimental physics, biology or chemistry research is never qualitative. How could you measure qualitatively?

You are right my friend Hanno about experimental physics, biology or chemistry. Other domains, such as Business, Accounting, Law, Information Technology, Arts, etc... can be qualitative or quantitative. Thank you for your comment.

Dear Hanno and Mahfuz.

I do not quite agree with your point of view, which concerns the impossibility of qualitative evaluation research in selected fields of science.

For example, chemistry.

But is not a qualitative assessment of research in the field of qualitative characteristics of new materials. So they can be measured quantitatively, but that the qualitative characteristics: flexibility, strength, odor, color, ....

For example, biology - the study of the quantitative impact of population on the quality of her life. Or as some kind of change (qualitatively) in the process of evolution.

And here again we can say that the quality is described by some quantitative characteristics. But so is the quality and quantity are interrelated.

And such examples in all fields of science.

It depends on the area of science, if your field is science then qualitative research is hard to conduct, it must be quantitative. However, sometimes it depends on the question you are asking. If the question you asked require a qualitative measure it can be done. In my experience all research should be in a way or in another be converted to quantitative, otherwise interpretation and generalization would be poor.

Dear Vyacheslav,

interesting points. But I want to contradict to your arguments.

Take your example from chemistry: Color, odor, flexibility, strength can be measured quantitatively. You just don´t need such precise result, to go on with your work.

Or biology: You can measure the genes by quantitative techniques (if you need it).

So my estimation in natural sciences is: you can work quantitatively, but you must not.

 In the other fields, which dear Mahfuz stated, quantitative research is often impossible or very difficult. So the researchers must rely on qualitative methods and try to improve their results by statistical methods.

My result: Researchers try to work quantitatively, but some times qualitative estimations are guiding or sufficient.

Dear Hanno.

I totally agree with your updates.

But you also confirm the idea of the unity of quantitative and qualitative methods. Therefore, each of us is right.

Moreover any examination precedes analysis of the literature. This quality piece of any research.

Dears @Hanno Krieger & @Vyacheslav Lyashenko  

Both of you speaking the same language but with different words.

i do quantitative research using SPSS package. Quantitative gices facts and figures for evidence.

I also do both. Usually I use the qualitative to get a general idea, and it usually precedes the quantitative one, which gives a more precise insight into the researched topic applied at the level of the researched population.

Most of the time, I do quantitative research.  I learned my statistics from a wonderful quantitative expert.  But recently I collected data by interviewing my respondents.  I think the qualitative data supports the quantitative evidence.  Do you agree?

My area of research i.e. Natural Product Chemistry entails both qualitative and quantitative research. Basically qualitative research is subjective and quantitative research is objective. Actually, research in any field involves varying degree of the two approaches. Quantitative research looks for explanatory laws and measures what it assumes to be a static reality in hopes of developing universal laws whereas qualitative research aims at in-depth description and is an exploration of what is assumed to be a dynamic reality.

Dear all,

there is not really a dissapointment between dear Vyacheslav and me, I just think, quantitative if ever possible! In the other cases estimation must help, supported by statistics.

Dear Hanno. Each of us has expressed its point of view. We did it in a civilized and open. At the same time we did not vote against it (as is done in other disskusiyu). And this is our truth with you. Sincerely, Vyacheslav.

The quantitative vs qualitative approach depends on whether you want to develop theory or test theory.    Whether you start from practice (bottom of pyramid)  or from settled theory (top of pyramid)

In a qualitative approach one investigates existing practice and seek to detect, observe, synthesize and define hitherto unobserved patterns from the data being examined.  You follow the data to where it leads.  Through this process new theories, new concepts, new relationships  emerges adding  to the body of knowledge

On the other hand, the quantitative approach begins with settled theories or models, and seeks to test hypotheses on the relationships in these theories/models typically in new contexts.   Through this process existing theories, models and relationships are tested adding  to the body of knowledge

I prefer qualitative research. I use indepth interviews of the sampled respondends, and enjoy the process of obtaining first-hand knowledge of the ststem concerned from them. I feel that the working of any system is difficult to grasp without in-depth interviews. In the process, some of my rerearches have also involved using aggregate quantitative data, which helped me to make some very interesting comparisons between the two sets of data. 

The research questions should always guide the scientific method.

Therefore, scientist should ask questions that they have the skills to answer. For example, I have no skills in physics because I am not trained in those methodologies, thus, I will not do research in that area using qualitative or quantitative methods.

I prefer to use the methods that is best for the research questions, testing the hypotheses might require either a qualitative or quantitative methodology.

It depends on the field of your research and the question you need to answer. Even if you are not clever in statistical analysis, you can ask for help of the expert. 

I do not think the question is in the correct perspective. The choice of the type of research methods depend upon the problem. It is not the question of one would have the choice. For example if I want to know the influence of feed rate in lathe turning on the surface finish produced, I can only use quantitative method, and there is no way I can use qualitative. Similarly if you want to know the some type of behavior of a particular bird, then it will be qualitative. It is the research problem that will decide the type research problem you would like to choose.

Dear Nageswara,

Certainly, the nature of research and especially, the research problem, would define whether we go for qualitative or quantitative research.

Both are necessary; only each gains higher significance over the other in particular contexts. Research which seeks to quantify and measure specific variables in a structured manner, and usually seeking a large sample size to gather more accurate statistical data will rely on quantitative methods. On the other hand, we also have exploratory investigations that may require hypothetical factors where exact data cannot be produced. These are usually the larger contextual variables that reflect general trends that help define the issue and develop a suitable approach to the problem, that is usually ill-defined at this stage. This favours a qualitative analysis approach and a wider range of data collection methodologies. 

The best works of research combine the two at different stages or even concurrently. It all depends on the topic, and on the researcher's willingness to do a thorough job.

For mathematics, quantitative, means based on measurements, coordinates, etc. Qualitative means topological and structural. Usually qualitative are more demanding.

An example where quantitative and qualitative methods are used is Catastrophe Theory.

In Statistics there is the ordinary quantitative one based on measurable data and there is also qualitative methods, used mainly in social sciences, which use Husserl phenomenological methods, recording data, etc. 

In Medicine a result needs to be supported by a statistical analysis. It may be not so for other fields of resarch.

In my work:  volcanoes, no way for qualitative approaches.  We have people and officials waiting for our data and recommendations in case of evacuation.

Dear Gustavo. So, there are some domains, such as Volcanoes researches, which can only be done in quantitative type of research.

I agree with most of the above respected comments;  but I believe that researchers have to have the capabilities and skills required for both types even though some prefer one on another OR some cases derive and force you for the appropriate method. A good researcher should have the eagle eye for the different types.  

In science their are many situations where only qualitative work can be done. This happens in the early stages of the research when we know very little about the subject matter or when we are exploring the broad whole picture of the research topic. With time, and as we get to know more,  research become more focused and more conclusive. So, research starts qualitative in its early phases  and ends in the later phases quantitative.

The choice of the type of research methods depend on the problem and field of expertise of researcher. Both types are important, but  It is not really a choice we decide on!. I do quantitative research in civil engineering as my field of expertise dictates it.

There is relevant article with 640 citations in Education researcher (impact Factor:2.779 | Ranking:6/219 in Education & Educational Research)

The attached links are also relevant:

http://www.snapsurveys.com/blog/what-is-the-difference-between-qualitative-research-and-quantitative-research/

http://www.surveygizmo.com/survey-blog/quantitative-qualitative-research/

http://edr.sagepub.com/content/16/7/16.short

Quantitative!

Easier to subject to statistical analysis!

Period!

Qualitative research is far more difficult and time consuming, and if properly done would provide a better understanding. The famous example is the Dame Jane Goodall, the British primatologist and her study of the African Chimpanzees. There is no way it could have been quantitative. I am giving here a link to the presentation that provides an overview of all the research methods and their applications.

Data ResMethods-Nature of Research

Dear Tobias,

May be quantitative research is easier to researchers who know statistical analysis, but it may be difficult to those who don`t.

Dear Mahfuz

We make sure that all research students at least register for one course on statistics as a main requirement. Statistical analysis is now become almost an integral part of research. In majority of engineering disciplines quantitative methods become a defacto research method and statistics therefore is part of that analysis.

Experimental methods and techniques, as well as statistics and statistical analysis , including (since ca. 1970)  the use of statistical packages are also an integral part of any serious study of psychology or sociology as a science. Thus such approaches are not confined to the so-called natural or physical sciences.

Moreover, this has nothing to do with the artificial, i.e. misleading distinction between qualitative and quantitative methods, which are a misnomer: not the methods but the data are qualitative or quantitative, and in order to analyze such data one has to apply appropriate methods and techniques, sometimes qualitative (weak measurement) sometimes quantitative (strong measurement).

However, I have to add quickly, that there are philosophically erudite scholars who deny or at least doubt whether psychology and sociology have achieved the status of a "real science", which of course raises the question how you want to define "real science" without getting into a circular definition. Any suggestions?

Dear Nageswara,

In fact, most universities (but not all) require students at least to register for one course on statistical analysis as a main requirement.

• some references to my previous post:

http://www.amazon.com/dp/0226449319

Here is difference between the methodologies from "Educational Research" by John W. Creswell:

Qualitative research is an inquiry approach useful for exploring and understanding a central phenomenon. To learn about this phenomenon, the inquirer asks participants broad, general questions, collects the detailed views of participants in the form of words or images, and analyzes the information for description and themes. From this data, the researcher interprets the meaning of the information drawing on personal reflections and past research. The structure of the final report is flexible, and it displays the researcher’s biases and thoughts.

Quantitative research is an inquiry approach useful for describing trends and explaining the relationship among variables found in the literature. To conduct this inquiry, the investigator specifies narrow questions, locates or develops instruments using statistics. From the results of these analyzes, the researcher interprets the data using prior predictions and research studies. The final report, presented in standard format, display researcher objectivity and lack of bias.

Dear Nageswara,

You differentiate between quantitative research and qualitative research in a nice way.

We should stress Phenomenology and qualitative research:

See,

http://en.wikipedia.org/wiki/Interpretative_phenomenological_analysis

Moustakas, C (1994) Phenomenological research methods London, Sage

CHAPTER 10

Qualitative Research Designs

http://health.prenhall.com/nieswiadomy/pdf/NIESWIADOMY10.pdf

Basically, summarizing what I have read before, the question seems to be, how to proceed in the long run - if at all relevant and possible - from qualitative data + methods to quantitative data + methods, and back again.

That means, we have at least a two-way classification of research approaches in scientific disciplines, where I subsume all scholarly and engineering activities under the umbrella of  'science':

• dimension 1 : type of data:: from purely logical to purely numerical
• dimension 2 : type of method :: from purely deductive to purely inductive

I will refrain from trying to give my own definitions of the basic terms logical, numerical, deductive or inductive. First, fully adequate definitions can be found in any elementary textbook or wikipedia. Second, people may have slightly different conceptions or preferences how to express the underlying dimensions. Third, a really productive and constructive discussion of the contents of these terms would require a more or less comprehensive enumeration of actual research fields and disciplines, something completely beyond my capabilities at the moment.

However, I have several hypotheses regarding the relevance and occurence of different combinations of the data-dimension and the method-dimension in the scientific realm. I would welcome, and recommend, if anybody interested in this topic - especially young still largely unbiased scholars and researchers in the methodology of empirical sciences - would take up one or more of the following hypothesis and conduct research of different types in order to find out which hypotheses can be corroborated and which not (for the time being).

hypothesis 1:

• There is no inherent quality difference or ordering on dimension 1, i.e. going from a logical to numerical type of research one will find both bad and good research at any point on this dimension

hypothesis 2:

• There is no inherent quality difference or ordering on dimension 2, i.e. going from a deductive to inductive type of research one will find both bad and good research at any point on this dimension

It would be necessary at this point to get more precise about what counts as good and what as bad research. Proposing and sorting out relevant criteria however is part of the research aimed at verifying both hypotheses.

hypothesis 3:

• There is no inherent requirement to position one's research at any specific point on dimension 1 and dimension 2, i.e. with respect to almost any scientific subject you may choose a more logical or a more numerical approach, and a more deductive or a more inductive approach. Usually the choice will depend upon personal interests, available resources and of course the goal of the study. But even then there might be several options.

hypothesis 4:

• given a specific research question within a given field of research, the choice of a particular type of research mainly depends on factors like personal cognitive capabilities and preferences and the bulk of closely related, already existing and published research results.

hypothesis 5:

• innovative research is possible and often necessary (in order to make any progress at all) invoking any combination of research approaches along dimension 1 and dimension 2, i.e. sometimes we will observe a steady increase in quantification (measurement), sometimes the reverse, sometimes we will observe a clear increase in theorizing (deductive style), sometimes we urgently need more experiments (inductive style).

hypothesis 6:

• a mature discipline is characterized by a balanced share of logical versus numerical, and deductive versus inductive style of research and its repository of results (in whatever form), i.e. an immature field is usually characterized by an overemphasis on certain reseach styles to the neglect or even boycott of certain other research approaches, and thus to a clear methodological imbalance.

And so forth. I am sure that a host of detailed research hypotheses can be derived from these initial, still broadly formulated hypotheses. And I am sure that some of those hypotheses require a logical analysis, others a rather numerical analysis, i.e. measurement, modelling and testing. Also, I am sure, that one sort of detailed research questions concerns questions of a theoretical nature (deduction, consistency, Ockam's Razor), while others can't be answered without doing some inductive (incl. abductive) type of research, i.e. observation, action, experimentation and the like.

Any suggestions from your side?

Both qualitative and quantitative research is important. Any one sided research may not be a balanced one as quality is significant and so is quantity, which can be analyzed statistically and give a sizable dimension to the work!

Just for the record: please note that quantitative research doesn't automatically or necessarily mean statistics-based research. Statistics, i.e. the application of methods based on a probabilistic framework, is fine if you deal with and are interested in phenomena which in some way obey the tenets of probability theory (frequentist, bayesian, personal, or whatever). But the field of quantitative research approaches is much much larger than that: some systems can be modelled fully adequately from a deterministic point of view, and some other systems require an approach based on Fuzzy Logics, e.g. Fuzzy Sets (Zadeh, 1965). Also, there are mixed approaches combining probability and fuzziness. Let the phenomena speak (Husserl): they dictate what you need. And if you can do without quantification (numerical modelling and measurement), well, that's OK, go ahead, adopt some logical approach (left side of the first dimension)

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Noted added on 2014-07-20:

Even in theoretical physics it is no longer self-evident or required to assume (as Quantum Physics has always done) that nature is inherently probabilistic. Recent developments have shown that all fundamental phenomena can equally well described and explained by purely deterministic models, i.e. causal models in which probability enters at most as measurement errors, but not on the conceptual-structural level. This will be good news for all those of us who have always had problems with understanding those strange probabilistic quantum logics or accepting that nature acts randomly, e.g. Einstein when he expressed his belief that "God doesn't play dice".

@ Paul, agree with your view point.

Dear Paul, Thank you for your thorough answer. You have given good details on the qualitative and quantitative researches.

Note added to your answer is interesting. "Recent developments have shown that all fundamental phenomena can equally well described and explained by purely deterministic models"... i.e. with quantitative analysis.

Would the results of the quantitative research be more convincing than a qualitative research.

Dear Mahfuz, 

this is so because the prejudice that scientific is only the one that can be measured. But today the theory of measurement is so general that one can say that qualitative approach coincides with these generalised measurements. In order that the scientific community will appreciate that we need a lot more time!

it is hard to prefer one over another.

sometime the research problems needs the mixed method of both quantitative and qualitative. So, the preference and domain of selection depend upon the problems and framed research questions.

Happy Questioning...

Whether qualitative or quantitative, I would prefer to conduct research that could lead to useful and beneficial outcome, address certain pressing problems and meaningfully supplement the existing knowledge  on the aspect.

Which type of research do you prefer to conduct: Quantitative or Qualitative?

Actually I like all three i.e. Quantitative, Qualitative & Mixed Methods Study because each category has its own strengths & weaknesses that is appropriate for certain research condition.  I started from quantitative and gradually like mixed method & qualitative.  Think the preference for a particular category also depending on a research's requirement (i.e. research problem, objective & questions) and researcher's skillset.  Agreed there are various techniques & designs in each category to learn but don't give up - we just need times to understand the general ideas for all techniques / designs but extract the relevant for our research use.  Through actual research practice, we will develop the love for those techniques / designs.

Both are very important, the choice of research type depends on the research question and problem. Some issues can only be of a Qualitative nature and some of them are Quantitative done. Personally, I like more Quantitative research.

Agree With Mohammadreza Bachari Lafteh