Major Data Analysis Approaches for Writing a PhD Dissertation

Writing a PhD is nothing less than a nightmare. Both quantity and quality of the data your need to gather for your dissertation will haunt you. But you don’t need to worry. Today I will discuss the major data analysis approaches you can use in your PhD dissertation. I hope you will enjoy reading the article.

First things first, let’s define the term data analysis. Data analysis is the process of analysing the collected data. It is also used to extract useful information from the data. The extracted information from the analysis will help agencies make good decisions about the issue.

 

Major Data Analysis Approaches

There are several major data analysis approaches currently in use. The choice of a particular technique depends on the aim and goals of your PhD dissertation. The basis of all the major data analysis approaches is two approaches. Those two approaches are qualitative and quantitative. In a qualitative approach, the data consists of words and descriptions. There won’t be any numbers to play with.

On the other hand, the quantitative data comprises numerical entries. This data is objective in nature, and researchers can analyse it very easily. Moving on towards the methods of major data analysis approaches. A brief description of the methods is as follows:

 

Descriptive analysis

The descriptive data analysis approach is the starting point of any analysis. It answers the question, “what happened.” The researcher orders, manipulate, and analyzes the data. The descriptive approach will explain everything about the data. Descriptive analysis is essential to perform as it tells the researcher to present the data in a useful way.

This analysis will not answer future related questions. The results of the analysis won’t tell a researcher about future predictions. In fact, it is just to explain “what happened” in your PhD dissertation. The researchers can use cluster and regression analysis methods to perform this analysis.

 

Exploratory analysis

As the name suggests, the researcher will explore the data in this data analysis approach. The researcher will now look into the data deeply. The researcher will also explain the relationship between the data and different variables. Once the data analysis completes, the researcher can find connections between the data. The researcher will also generate hypotheses and present solutions to the problems.

The PhD dissertation is about a specific issue or problem. The exploratory data analysis approach helps the researcher give a solution to that particular issue. Data mining is the typical area of application for this data analysis technique. Researchers use data mining techniques to explore things.

 

Diagnostic analysis

The diagnostic analysis is one of the most powerful data analysis approaches. This analysis approach answers the question, “why is this happening.” It gives analysts a firm understanding that why this issue is happening. The above two and this data analysis approach enable a researcher to solve the problem. It is because the above two analysis approaches explain “what.” This particular analysis technique explains “why.”

Therefore, when a researcher finds answers to the “what” and “why” of a problem, the problem solves. The researcher now has to propose different solutions to tackle the issue. The researchers may use regression analysis to conduct this analysis.

 

Predictive analysis

Another data analysis approach is predictive analysis. This approach answers the future happenings, i.e., “what will happen in the future?” To predict the future, the researcher uses the results of the previous three methods. The techniques of machine learning and artificial analysis can also be employed to predict things.

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In a PhD dissertation, there will also be a section about future happenings. This section will discuss the implication if the problem is not solved immediately. The researcher uses the predictive analysis approach to overview future happenings. For predictive analysis, researchers use neural and cohort data analysis methods. The regression analysis can also be used to predict things.

 

Perspective analysis

The perspective analysis is another most effective type of data analysis approach. This approach answers the question, “How will it happen?” You will be using this type of analysis to fix emerging issues in your dissertation. It will also tell you how you will fix those issues. The method that is mostly used to do perspective analysis is factor analysis. In factor analysis, you take the perspective of others about a product or service.

 

Conclusion

I would say it’s possible to convert raw data into information using the right data analysis method. I hope this article enables you to have a clear idea about different analyses methods.