Strengths And Weaknesses Of Quantitative And Qualitative Data Philosophy
Human science or social science is the academic disciplines that study human behavior while history is the study of the past. To propose a claim, social scientists and historians usually use inductive logic to generalize and create their theories. They need to have their set of data first before they can proceed to their claims. The data itself can be divided into two, which are quantitative data and also qualitative data. Quantitative data are number-based data which can later be used in further calculations, and are mostly from experiments conducted. They are usually being measured using apparatus used, and they have their own units that are approved widely. Meanwhile, qualitative data are the data that can be observed by our own senses; smelling, touching, hearing, seeing and tasting. It can be anything that can be observed in the experiments handled. Colour, sound and even smell - all of these things can be put under qualitative data group as they do not have their own fixed units that are used in measuring them. Both of the qualitative and quantitative data have their own limitations and also strengths. As for human science, all of these will be discussed later according to the method for human science experiment as called by philosophers as Verstehen. We will also see which type of data is being used more in making researches either in social science and also history.
In human science, for quantitative data, the variables of the research conducted can be easily identified as it starts off with making hypothesis and theories first before the research can be done, thus making it deductive. Rather than directly proceed with the experiment, the social scientists tend to propose their own theories first. They need to identify the variables first, and after that only they can measure the relationship between those variables. Quantitative data in human science usually can be gotten from interviews and reviews, which can be described as experiment-based. They data will be used for further analysis, which will lead to their conclusion in forms of generalizations and predictions. These are all what quantitative data means.
On the other hand, in gathering qualitative data, the researchers need to conduct their research first before they can get their hypothesis and theories which makes the research inductive. They usually look for patterns among their subjects in the research, so that they can later make their conclusion based on the patterns gotten. The research cannot begin with hypothesis and theories like in quantitative-based experiment, as the variables are more complex to be identified, making it difficult for the social scientists to measure the relationship between them. Generally, the qualitative data which is usually obtained from surveys is used for making contextualization and predictions. From the explanations above, we can clearly see that both type of the data; quantitative and qualitative, have their own limitations and also strengths which can either support or weaken the knowledge claims in human science.
Basically, experiments in human science are all about making observations since they are dealing with humans' behaviors. Instead of fully relying on qualitative data, the researchers can also use quantitative data in emphasizing the claims they made. For human sciences, observations are not the only things that the researches look for. The Verstehen states three falsifications in observations: 'Seeing what can't be seen', 'being seen by the seen', and 'seeing what you want to see'  . These three falsifications are the things that are need to be concerned of. The first falsification; 'seeing what can't be seen', states that researchers may only be able to analyse by themselves a certain kind of data. They can only observe the things that can be detected by their senses. But what about seeing the things that are abstract, the things that cannot be counted numerically? For example, one of the behaviors that can be concerned in human science is motivation. But, can we really see the motivation itself? Does it appear to be observable physically? This is what I mean with the things that cannot be seen. People might say that person A is very motivated. But, how 'motivated' is considered as motivated? Motivation is something subjective, where different people might have their own different interpretation about motivation itself. Hence, this proves the limitation of the data in the social sciences in supporting the knowledge claim brought. As humans' senses are limited, the data gotten from observations may be accurate, but they also may not be precise.
The second one; 'being seen by the seen', shows that the subjects will act differently depending on whatever they are being tested with. A subject who is being monitored by a teacher would act differently with a subject monitored by a psychologist. People tend to behave the other way around just to satisfy or to be against the assumptions, the predictions made by others. This might end up with a conclusion that looks like it has already being 'planned'. A social scientist's prediction of human behavior might influence the human behavior. For example, when a psychologist would like to see whether the bad attitudes of the students in a particular school brings about the bad results of the students or not, the students there might act nicely while being observed. Hence, this makes the experiment a failure.
The third falsification method; 'seeing what you want to see' shows that in human science, the researchers themselves are also playing their own part of the test as they might be testing something they have experienced before and through the experience, they can later develop their own individual certainty. The observations that they acquire might either oppose or even support their quantitative data and also, how strong the quantitative data support the observation will be essential to the researcher as the quantitative data are the data that most would prefer to be shown. Hence, we can say that the quantitative data helps in supporting data when the data is parallel with the observations. Oppositely, when it comes out as a negation to the observations, then it would cause a lot of uncertainty.
Scientists make their own different perceptions towards qualitative and quantitative data in order to know which one of them is better and should be used in conducting experiments in social science. Social scientists Lincoln and Guba (1985) and Schwandt (1989) perceived that both qualitative and quantitative data are incompatible to each other, making them not suitable to be combined in making researches  . On the other hand, Cook and Reichardt (1979) and Patton (1990) believed that skilled researchers can actually combine both to get better outcomes  . The argument usually becomes mixed-up because both the positivist (quantitative) and the naturalist (qualitative) paradigms rest on different assumptions about the nature of the world, making them to require different instruments and procedures to find the type of data desired. This does not mean that the positivist never uses interviews and reviews in their researches, or that the naturalist never uses a survey. They may, but such methods are supplementary, not dominant. Different approaches allow us to know and understand different things about the world. Hence, we know that using both qualitative and quantitative data in researches is better as the one's weakness can mutually be covered up by the other one's strength.
In history, we can say that most historians depend more on qualitative data as the hypothesis and theories are actually gotten at the end of the researches. Historians apply induction techniques when it comes to make conclusions. The advantages of qualitative data itself actually help historians in supporting their knowledge claims. History is an area whose variables are hard to be identified, hence making the researches which are being dependent on qualitative data almost impossible to be done. Historians usually look for patterns in their findings, and in doing this, qualitative data is more suitable to be used compared to quantitative data. Furthermore, history is majorly about making up stories and making interpretations towards the subjects. With quantitative data, we cannot actually interpret the situations that had already happened in the past, but it can be done if we use qualitative data. But, there are also certain circumstances where the historians apply the use of qualitative data. For example, qualitative data is being used when the historians are undergoing carbon-dating process. Hence, from the statements given, I could say that in history, historians tend to depend more on qualitative data rather that choosing quantitative data.
Hence, as a conclusion, we could say that qualitative and quantitative data have their own strengths and also limitations in supporting the knowledge claims in social science and even in history. The difference between these two areas of knowledge is that it would be better for social scientists to use both qualitative and quantitative data in making their researches whereas in history, the historians tend to rely more on the qualitative data compared to quantitative data in making up their own conclusions, their own interpretations towards their subjects.
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