Social will investigate a theme through a traditionally scientific

Social research can be defined as: the way we go about finding explanations for human behaviour in different social contexts. Social research is important as findings can be used to critique existing policies and/or help to implement new ones that bring about social change. The ‘way’ we do this, or ‘methodology” we use can vary. However, all methods are likely to come under one of two groups: quantitative or qualitative. A quantitative method will investigate a theme through a traditionally scientific approach taking an objective standpoint mainly through collection of numerical data. In this case, demographic changes can be considered quantitative (though the reasons behind the change may be qualitative). On the other hand, a qualitative method takes on a more subjective approach that allows a wider range of data collection around a topic. For example, open questions in interviews can be considered qualitative.

 

In the following paragraphs the advantages and disadvantages of both quantitative and qualitative research methods will be explored, analysed and evaluated, and conclusions will be drawn from this.

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Quantitative research methods provide a highly scientific methodological backbone to any research. The use of numerical data can increase the objectivity of the results. In this sense, quantitative methods are positivistic i.e. it is “concerned with positive facts while excluding speculation” (Dictionary.com, 2012).

This is a major advantage for social researchers as many projects in the social field are high in subjectivity rather than objectivity, in other words the findings can be more easily manipulated depending on the researchers view. In comparison, quantitative data can’t be manipulated as easily due to the numerical format which doesn’t change. It is this that helps bring social research into accordance with the more traditional sciences of physics, biology and chemistry. Increased respect and validation of results under quantitative methods makes conclusions easier to draw through similar analysis techniques used in the traditional sciences mentioned. Or as Gilbert puts it, quantitative methods “allow us to generalise findings, explain phenomena by citing casual relationships” (Gilbert and Stoneman, 2008, p. 80). The findings can then be exposed to different environments or people to see if the theories still hold. These ‘casual relationships’ can then be altered where specific models can be developed and assigned to different contexts based off the original ‘casual relationship’.

 

It is these previous points that allows quantitative method research to be viewed highly in terms of its epistemology. This is defined as the “theory of knowledge, especially with regard to its methods, validity and scope, and the distinction between justified belief and opinion” (en.oxforddictionaries.com, 2018).

Using a quantitative method to collect data is often fast and simple. The vast amounts of quantitative research are done via surveys where the same questions are asked to a large sample where there is little planning needed in the administration process. This means vast amounts of people can be reached whether it’s over the internet or in the street. This provides a varied data set which is likely to be more representative of the wider target population. A wide scope can also be found in a wide range of social research in which quantitative methods can be incorporated, for example psychological studies often use controlled laboratory environments while government surveys can use more natural environments such as a busy high street. The scientific thinking which analyses data and forms conclusions which in turn creates the evidence-based justified beliefs that we strive for in research. Alan Bryman describes the need for raw data to be ‘checked and managed’ while quantitative methods are used when “coding and transcriptions are used to analyse data” (Bryman, 2016, p. 11). This signifies how accuracy is at the forefront of quantitative methods.

 

Further advantages of quantitative data can be found under the practicalities, ethics and the ontological background that forms the quantitative position. Ontology can be described as “a set of concepts and categories in a subject area or domain that shows their properties and the relations between them” (oxforddictionaries.com, 2018). The approach of both ontology and quantitative methods overlap in a number of areas. One of which is objectivity; ontology looks ‘laws’ within a subject area where such concepts need sufficient backing by empirical evidence to be able to be considered, this is where quantitative methods come in with a scientific methodology and objective data analysis where conclusions and be confidently drawn to give concepts the necessary objective evidence. Both approaches can be said to approach research from a deductive angle, this is where theories from within the subject area are used “to guide data collection” (Alcock and Becker, 2016, p. 16). Gilbert provides further support for this: “quantification as a way of the nature of social reality” (Gilbert and Stoneman, 2008, p. 82) i.e. without quantitative data backing research it is unlikely to be considered in the social research climate. Additional advantages of quantitative data can be seen in their practicalities. Quantitative methods are very cost effective especially in natural settings while large samples/data can be collected due to the time efficient of collection methods such as surveys.

 

There are also negatives when using quantitative methods. One of main downsides is that the method relies on a controlled environment where only certain variables change. This makes the results unrepresentative of the real world: where extraneous variables can have a dramatic effect on social behaviour. Due to the quantitative method, the independent variable which changes the dependent variable might not be found. This leads on to another downside of quantitative methods: correlations. Quantitative methods typically use correlations to show the relationship between 2 variables, however correlations themselves can’t show the effect the variables are having on each other, only the resulting outcome. This is therefore a reductionist view of conducting social research and limits the real-life application of any results as a complex scenario is often reduced to a few factors resulting in unrepresentative conclusions. For example, when looking at illness a certain medicine may look like it helps to kill the bacteria, however outside with pollution the medicine may not work as these external factors haven’t been accounted for.

 

Quantitative methods also use closed questions as the predominant way of collecting data, this has negatives as these questions often limit a participant’s response to a couple of words. This is therefore not sufficient when research is being undertaken surrounding subjective topics, where a short answer can’t fully explain someone’s reasoning; quantitative data tries to quantify often subjective areas thereby missing essential details. Gilbert explains the limitations of quantitative methods in “describing and exploring the full extent of social reality” (Gilbert and Stoneman, 2008, p. 80).

 

Other Limitations of quantitative methods come about in the form ethics and practicalities. When using surveys to collect data the researcher must make sure the questions abide by general ethics. These notably include privacy, consent and the right to withdraw. These are important as quantitative methods generally use controlled lab environment where ethics can be tested. For example, a participant of a study may feel intimidated by laboratory environment especially if it’s at a prestigious university and so may feel obliged to give consent and take part though they may not feel comfortable. A famous example of where ethics were broken was in Milgram’s study of obedience. This study took place at Yale University and tricked participants into giving fake electrical shocks to measure obedience to authority, major questions were as the participants were “exposed to extremely stressful situations that may have the potential to cause psychological harm” (McLeod, 2007). When undertaking unethical research Gilbert asks: “Do the benefits outweigh the risks involved?” (Gilbert and Stoneman, 2008, p. 204) in the case of Milgram they certainly do as many important conclusions were drawn from that study as it was one of the first of its time. However, it is unlikely anything like it will be allowed again.

 

Alternatively, qualitative methods try to provide a detailed explanation of a social phenomenon or as Keith Punch describes qualitative methods “aim for a holistic view of context from ‘inside'” (Punch, 2014, p.118)

This outlines one of the main advantages of using qualitative methods over quantitative: detail.

Collection of data for qualitative methods usually involves asking participants open-ended questions which allows for detailed responses showing the participants own personal view about certain matters. This provides huge amounts of textual data collected straight from the participants who are able to fully express their own opinion/reasoning behind what they have put down. This therefore allows a range of factors to be analysed which may not have been considered if a quantitative method was used. This also makes the answers more representative and applicable to the ‘real world’. This is because qualitative methods aren’t confined to a controlled environment but rather research can be at the heart of a theme where it is fully immersed in the context of the study. Examples of potential qualitative methods could include surveying members of a community about their opinion of the implementation of a new policy or observing behaviour among people in different communities.

 

Qualitative methodology comes under a different epistemology to quantitative methods as it moves through positivism towards interpretivism (En.wikipedia.org, 2018). Traditional positivist theories (quantitative) lacked the understanding of “human interaction”, however now “interpretivists are apt to draw meaning from the subjective experiences of individuals engaging in social interaction” (En.wikipedia.org, 2018). These “meanings” represent ‘true’ findings from a natural environment which can then be used for accurate policy creation as the findings drawn from the research give a precise representation of the real world. Due to this “subjectivist epistemology”, the researcher is said to be “linked to their research” due to the interpretivist nature while qualitative methods are also said to have a “relativist ontology”: “perceives reality as intersubjectively that is based on meanings and understandings on social and experiential levels.” (Dudovskiy, n.d.). This gives an advantage to qualitative methods over quantitative as it gives an accurate representation of all factors involved.   

 

However, there are also negatives to using qualitative methods. One of these is the difficulty to analyse and categories subjective data. This is prominent when a team of researchers come together to analyse data they have collected, during the analysis each researcher may have different ideas about the findings the data shows which can lead to confusing or in complete conclusions. Ethics of the research can also be questioned, especially if the findings are likely to have a political impact or if any of the researchers are being financed by government organisations which may lead to a political motive. Also by grouping qualitative data together based on similarity, may lead to the loss of the individuality of the data, therefore restricting each answer’s detail and nullifying the potential advantages qualitative data has over quantitative.

 

Other weaknesses surround the practicalities involved when using qualitative methods. These include cost and time. The cost of a qualitative method is likely to be higher than a quantitative alternative because of the additional complications involved, such as setting up one to one interview with participants. These can also be seen as very time consuming especially when added to the extensive analysis needed for the detailed data that is collected. Keith Punch also adds that data collected via this method if “often not generalisable” (Punch, 2014, p. 122) as it is often collected in small data sets, due to its costly nature. This therefore leads to conservative findings which represent the sample but are unlikely to represent the wider population as a whole; any conclusions ultimately can’t be generalised to everyone, thereby limiting the applications of the research.

 

In conclusion, both qualitative and quantitative methods hold strong arguments as to why they should be favoured over each other, with the strengths of one usually countering the weaknesses of the other. It would therefore make sense to use a mix methods approach which incorporates both methodologies. This would allow for detailed answers but also easier analysis. Ensuring strength in critiquing policies and a more evidence based approach to social change.