Wednesday, September 22, 2021

5 Most Common Techniques to Analyse Secondary Data

Data that is collected from a second-hand source like internet is termed as secondary data. Secondary data helps to save time and money. The researcher picks up data related to their research question and study. In simple words, data is collected by indirect means. Research on secondary data is the sharing of data. It can be more than one time. This method makes compiling easier. You do not have to invest your efforts in the collection of data.

In the same way, if you go for primary data rather than secondary data, you have to spend lots of time on the data collection. Also, you have to collect data on a larger scale rather than a small scale to ensure accuracy. You have to invest time in the form of money. But secondary data saves you from all these efforts. After collecting the data, you have to analyse the data as well. To analyse the data, researchers of a PhD dissertation writing service have shared here a list of 5 most common secondary data analysis techniques:

Comparative Analysis

Comparative Analysis

Comparative analysis is the comparison of things. It could be in the form of documents, data samples or processes. Comparative analysis cover pattern analysis and decision-tree analytics. In this, you can compare past and currents reports, images, charts, graphs and tables. In research work, you interrelate your work and analysis with work that other researchers have already done. In such a case, you must use a comparative analysis technique to see the same or different points.

By using the comparative technique, you can easily plan and refine your work. Here you can again save your time because you get to know about the work structure at the initial stage. You can also cover up the gaps of past study, with which you are comparing your work. In this way, your research can lead to past researcNext, youYou can make a general pattern of your work by comparing your data. Then, you have to apply your tests and statistical methods to find out the resemblances and variances in both works. You can do this all by using a few empirical case studies.

Content Analysis

In content analysis, you do not have to go for experimentation or statistical method or approach. The statistical approach is only applicable when you deal with the coded text. Here you check out the pattern of communication. You can do this by going through some document, report, picture or any video. By following content analysis, you can determine the psychology of a person and then the participant's emotional state. It is easy to identify the trend of the communication. For content, analysis is collected in the form of interviews. Open-ended questions are very important to add for content analysis. In conceptual analysis, you only rely on the text. It allows you to do qualitative as well as quantitative approaches. For example, you can check out the cultural insights in the document in an easy way. In conceptual analysis, you discuss models of humans and their different kinds of thoughts. Also, you can have an idea of organisational behaviour. If you compare your work with other research work, it makes your work more powerful.

The content analysis further has two categories like conceptual analysis and relational analysis.

Conceptual Analysis

Conceptual Analysis
In conceptual analysis, you have to determine the pattern of concepts discussed in the text. Check out which point is on repeating and is also very important in the text.

Relational Analysis

In relational analysis, you find out the relation between different concepts discussed in the conceptual analysis. This approach leads you towards the results of the research.

Systematic Literature Review

In a systematic literature review, you have to collect all strong pieces of evidence related to your dissertation. But these pieces of evidence must be from an authentic source. In a systematic literature review, the best thing is to cover the research gap of other studies. First of all, you design a research question for your research work. Secondly, you collect all the available evidence and finalise the authentic one. Finally, you collect the solutions to cover up the gap of study. Then, you can go for the major characteristics of the pieces of evidence and demographic characteristic of the past studies.

Grounded Theory

Grounded theory is based on logical reasoning. You cannot use your assumptions for the study. But there must be some facts and figures for the analysis. Grounded theory helps you to understand the past phenomenon. By doing so, you can easily check out the development in the current theories. With the help of grounded theory, you can do a good investigation of any dissertation. It helps you to know the nature of the content. You can easily identify the conflict points between the two studies. As assumptions are not allowed, you can find out the exact happenings related to your dissertation.

If you are interested in going for grounded theory, you need to have expertise in it. Because of the large number of data, you may not be able to handle the data. In addition, grounded theory does not have specified rules and regulations.


Meta Analysis
According to a PhD dissertation help firm, meta-analysis is based on the critical analysis in the study. Here the analysis has precision in it. By using meta-analysis, the researcher can reduce the chances of inaccuracy and negative results. It helps you to find out the issues in the analysis. In simple words, meta-analysis helps to find out the effect of pieces of evidence. Also, you can check if the effect is positive or negative. Still, some of the researchers does not prefer meta-analysis because of its biased nature. Sometimes it becomes difficult for the researcher to manage homogeneousness in work. If there is some false or bad study included in the research, you cannot publish your research at any cost.


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