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What Are The Common Types Of Data Analysis For A Dissertation?

There is a lot that you will come to learn when you are in the process of writing your dissertation. Most of the time students spend a lot of time thinking about the introduction and the literature review, and forget about the important parts like the data analysis chapter. This is one of those chapters that will actually have a lot to do with the information that you present in your paper.

Just in case you have never really been able to think about the data analysis chapter before, you can go through this website and see the kind of information that you can learn in the process. You will realize that there is so much that perhaps you have never really been able to know about this chapter.

It is the chapter that makes or breaks your paper, so give it some serious thought. The following are the common types of data analysis that you are supposed to consider when working on your dissertation:

Descriptive data analysis

In this form of analysis, you are in a good position to describe the main features that make up the sets of data that you are using. One of the best examples of this kind of analysis is available in census data.

Inferential data analysis

This form of analysis lies in the use of different theories. As a researcher, your work is to test all these theories against a given framework, and then from there you can draw conclusions.

Mechanistic data analysis

A lot of students are often afraid of using this kind of analysis because of the fact that it does involve a lot of work. It requires the student to use as much time as possible understanding the changes that are available in the variables under investigation.

Causal data analysis

As the name suggests, this is a form of analysis that places an emphasis on looking at what happens to a given variable when something is done to another variable. In most cases it is used for data sets that are related in one way or the other.

Predictive data analysis

This form of analysis depends on historical data. You have to look at things that happened in the past, notice a trend and then use that trend to predict the future events.

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