Main peculiarities of a dissertation methodology structure

Methodology is a very important part of your dissertation. Some people also refer to it as research methodology. It is a section where you show your readers how you gathered your data that you have used in the paper. You need to show the tools and strategies you adopted for collecting the relevant information and then analyzing it.

These methodologies deal with the theoretical frameworks and tools you use to collect certain information or regard it as relevant or useless. Data that you use in your research paper can be of two types.

If your data can be counted in numbers then it is quantitative data. For example, 45% people are on diet in the Eastern Europe at any given time. The digit 45% is a quantity so this is an example of quantitative data.

If your data cannot be quantified then it is called qualitative data. Best examples of this are data based on demographics and attributes of a certain group.

In the research methodology, you need to talk about two things. One is data collection and the other is data analysis.

Data collection

The collection of data can be done in two ways. One is primary research or firsthand information. Second is secondary research or second hand information.

Primary research

Primary research is the direct data that you collect on your own. This could be done via interviews, surveys, and direct sources. This data can be classified in to structured, semi structured, and open ended data.

Secondary research

Secondary research involves data that you collect through indirect resources. This data is already present in books, journals, libraries, newspapers, government surveys and statistical reports etc.

Data analysis

The second step after collection of data is analyzing it. This is where you use theoretical frameworks or your school of thoughts to filter out relevant and irrelevant data. You also need to see which of the data is valid and collected from an authenticated source and which one is not reliable. The analysis of your data can be through content, statistics, disclosure, and semiotic analysis.

When you analyze your data, you need to see why you chose a certain research methodology over the other. You also need to explain why you did not take a certain method in consideration. Here are a few questions you need to answer while analyzing your data.

Why did you take an open-ended interview?

Why a certain group was not included in your survey?

Why you prefer interviews to journal articles?

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