Common Techniques to Analyse Qualitative Data for Your Dissertation
Qualitative research probes the softer side of an issue. It explores and describes the depth of that issue. It focuses on words, ideas, and concepts. If you are new to this, you might find it difficult. It takes you to the depth of the concepts. It also includes vast terminologies. For new researchers, it is better to know qualitative data first. Qualitative data is something that does not include numbers. It means that you are not bound by numerical values. Yet, it is not easy to deal with this approach either. It takes a lot of time to analyse this type of data. You have to mess with many field notes. This process is really hectic sometimes. In this article, we are going to share some common techniques to analyse qualitative data. These techniques help analyse both primary and secondary data types.
It is the simplest form of qualitative analysis. It observes the pattern within some content. The content may be of any kind. It includes text, images, or any other piece of information (Stemler, 2015). These include the speech of a prime minister, or letter to the editor of a newspaper. In content analysis, we focus on identifying frequency of the words. These words show the importance of different ideas according to their frequency. We also try to find the patterns that highlight meanings of the terms. In qualitative analysis, you have to stick with the main idea. Same is the case for content analysis. You have to remember the goal of your study. Otherwise, you will get distracted from the main work.
Content analysis also highlights the picture of quantitative data. Students use this method while dealing with secondary data. This is because we make codes, their frequency, and arrange them in tables. This also takes a lot of time. Students have a small amount of time to complete this. So they have to be careful before selecting this analysis technique. It is not an easy task to deal with a large amount of qualitative data. Students can also miss important points. It is better to understand those before choosing any of the research approaches.
It refers to analysing the words within their social context. It means understanding the words as they are spoken in the specific cultures, and societies. It gives a true understanding of the concepts and words. Culture has significant importance. We cannot ignore it when we analyse the concepts of this culture. For example, the dictator talks more about discipline. We can understand this by observing the social environment of their country. Discourse analysis helps us in identifying the effect of society on their concepts. So if you want to study a country’s culture, discourse analysis is the right way to do this. Don’t forget that it takes a lot of time. You have to clarify some borders before starting it too.
According to a dissertation help firm, this analysis is about listening to stories of the people. You try to understand the meanings of these stories. It helps in making a sense of the world. We find the meanings of their stories and relate them with reality. It is important to know how they can be narrated. So don’t ignore the gestures of a narrator. It means that we should not only focus on the story, but also on the way they tell them. You collect a small sample for this study. But you spend more time collecting qualitative data. This is because you have to listen to people’s stories. Its results take strong effect from the researcher. Hence researchers have to set aside their biases. Students can use this technique when they want to show a specific view of the world.
It is a commonly used technique for conducting qualitative analysis. It focuses on the meaning of patterns within data sets. We take a large amount of data for analysis. After that, we make different groups of the same patterns. Next, we identify the themes in the data. These themes help us in giving meaning to the concepts. We use them to analyse opinions, and experiences of the people (Terry, 2017). It focuses on exploring the available data. Most students use this analysis for their dissertation. It is a good choice for the students. This is because many students want to explore other people’s experiences. This analysis provides great flexibility. You can even change your research objectives during the research. This is the biggest advantage of thematic analysis for students. Students use this analysis due to the many benefits that it provides.
It is a powerful technique for conducting qualitative data analysis. Researchers use this technique to create new theories. You go with an open mind to deal with the data. You have not made any assumptions about the data. Hence you allow the data to show you something new. It means that your analysis moves from the ground up. You start from broad questions. Then narrow them down. After that, you can reach a specific hypothesis. This process enables you to develop the theory. It is the main characteristic of this technique. It has no drawbacks. Your biases may not affect this process. You should remember that this is not a simple task. For students especially, it isn’t easy to approach. The supervisor doesn’t suggest MS students to use this approach. Yet, they can adopt this same approach while pursuing their PhD. This is because they have enough time and knowledge to manage qualitative research at that stage.
Qualitative data analysis allows you to understand meanings of the concepts. You explore the issues in different ways. Qualitative analysis allows you to use different commercial management techniques. Content analysis is a popular technique in this aspect. You understand concepts through frequency of the words. The discourse analysis type focus on the words relevant to society’s context. Suppose you have to analyse the stories of others to give them meaning. In this case, you should go for a narrative analysis. Thematic analysis, and grounded theory are also used for this purpose. Students should choose the option with heightened care and focus. Otherwise, things might become difficult for them to manage.