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How to Analyse Secondary Data for Dissertation?

 

Data that another researcher has already collected is called secondary data. Due to technological advances and the accessibility of the internet to peer-reviewed publications and studies, secondary data is increasingly used as a method of data collection. Nevertheless, students often ask themselves how to analyse secondary data most effectively.

This blog post is created to guide students and researchers in analysing secondary data for dissertations.

The process of Data Analysis

The use of existing data is a systematic methodological technique with a set of precise procedures that must be followed to write a successful analysis. There are three basic steps to follow:

  1.     Formulating Research Questions
  2.     Choose the dataset
  3.     Writing up the Analysis

Formulating Research Questions

To use the dataset to solve research problems, you must use theoretical knowledge and conceptual competence when using secondary data. It follows that the first stage is to accurately identify and develop your research questions so that you know what areas of interest you need to investigate to find the best secondary data.

Choose the Dataset

The first step in this process should be to identify what is currently known about the topic, where knowledge gaps exist and what data is available to fill these gaps. Sources can come from academic studies that have already used quantitative or qualitative data; these sources can then be compiled into a new secondary data set. One advantage of secondary research is that original survey studies often use only some of the data collected, which means that this unused data can be used for different situations or viewpoints.

Writing up the Analysis

Depending on the method used, writing up the analysis after you have your data set may vary. If it is qualitative data, you should proceed as described below.

Read through all your material and note any initial conclusions, connections or themes and how these relate to your research questions.

Once the main themes are established, it is useful to go deeper and find related sub-themes that build on the main themes and correlations in the data set. This encourages the discovery of new perspectives and increases the originality of your work.

Presentation of the Analysis

The first paragraph of the introduction should contain a list of all sources. To ensure a smooth and neat flow of work, it is advisable to record the individual points in the order in which they appear in a table. The introduction should also concisely summarise the main findings and results.

Each argument or topic should have its subsection in the Main Body for secondary data, regardless of whether quantitative or qualitative data are used. A main heading for a core theme and subheadings for each of the sub-themes found through the analysis is a wise approach.

Regardless of whether primary or secondary data were used, all Results sections should include a reference to the research questions and previous publications. This is because mentioning previous work shows a deeper level of reading and understanding of the topic under study, regardless of whether the results support or refute previous studies. You can check Essays.UK for more information on the Data Analysis section for a dissertation.

To summarise the findings, the section of a secondary data dissertation should include a summary of the main findings and a conceptual framework that illustrates the conclusions of the research. This shows that you have a solid understanding of your secondary data. 

 

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