Analysis in Academic Research

Analysis in Academic Research – 7 Necessary Things to Avoid

Analysis in academic research cannot be without mistakes. Just because the section of your research is named as analysis, it cannot be an oracle. Similarly, finding a research paper on a glossy website with very attractive infographics does not mean that the data in its analysis section is free from mistakes. So, analysis is always prone to mistakes, regardless of how original and correct it is.

So, it is inferred that there are many things that you need to learn before running an analysis in academic research. The good news is that today’s article is also on the top 7 necessary things you must avoid while performing an analysis. However, before moving on to the actual discussion, let’s explain the meaning of analysis and its importance in academic research.

What does it mean by analysis in research? Explain with importance.

An analysis is the detailed examination of something in order to approve or disapprove it. It involves performing research using different research methods and separating the obtained results into smaller and logical sections. Those logical sections are then categorised into further smaller groups and guide the overall analysis. An analysis presents a specific argument about the research topic and then supports that argument with bulletproof pieces of evidence.

Let’s talk about the importance of analysis in academic research. A truthful and error-less analysis gives the reader insights into what the researcher has derived or inferred out of the entire data. It also helps to understand the interpretation of the results in the context of research questions. It means checking whether the research has answered all the questions or not. So, all these things make the analysis section important in research.

7 necessary things to avoid in analysis

From the discussion above, you now have a pretty good idea of the meaning of analysis and its importance in academic research. It is not enough because you can still fall into many pitfalls and unnecessary things. So, there is a need to learn the top 7 things that are necessary to avoid. Hence, a brief description of those is as follows:

1.      Unstructured analysis process

Having a structure to run your analysis is very important. What do most students do? They jump straight into the analysis process without any structure in hand and hence fail to do the correct analysis. So, you must avoid doing this. The analysis needs to be a structured process that begins with well-defined objectives followed by a strong hypothesis. Your analysis must answer “what” and “why” questions about the things you have learned from the analysis. You can hire a dissertation proposal writing service if you are stuck at this step.

2.      Overfitting on the wrong metrics

Overfitting in its actual definition describes a model that fits perfectly on a given set of data. Pretty good thing, huh? No, it is not good for the analysis in academic research, dear student. You must choose a model that fits the given set of data as well as predict future patterns. The reason is that unearthing the hidden patterns, themes, or trends is the primary goal of the analysis section. Therefore, do not overfit the wrong metric and use the right model.

3.      Presenting trends without context

Presenting charts, tables, and histograms without context is number-crunching, not an analysis. Note that there is always a story behind the trends in every dataset. This story can be a significant event based on which you have collected the data and analysed it. So, present this story in your analysis. It is also a sign of good analysis that it is rich in real-life events and stories that provide a context to the research. So, always present the analysis with some context.

4.      Being a slave to the average

In your analysis, do not be a slave to the average. The average here means the central value, which is easy to measure. However, sometimes calculating only the average of the data in your analysis in academic research can be costly. The reason is that the segmentation of the data and its categorisation is necessary, and this cannot be achieved by only the average. As a researcher, you must also calculate mean, median, mode, variance, standard deviation, and skewness.

5.      Standards are not much important

Avoid following the standards always. In my 6 years of academic research experience, I have seen that the student researchers mostly run toward the standards. What is the standard for this metric? Is this obtained result in accordance with the standard or not? These are not the right questions to ask, and you must avoid asking them. The analysis in academic research is good as long as it does not conflict with the research questions. So, forget about the standards and pay attention to the attainment of your research objectives.

6.      Do not jump to conclusions early

The analysis section of academic research is not the conclusion of the research. Come out of this, students, and do not try concluding the research topic in the analysis section. Instead of a conclusion, just focus on the analysis and relate your analysis to the research questions, aims, and objectives. Interrogate every data set in your analysis with the question “why”, and do not try to give unnecessary verdicts or final remarks.

7.      Resist academic bias

Analysis in academic research is prone to academic bias because it is a self-reflection and self-perspective of the researcher. So, over-emphasis on one part of the research can result in bias in your academic research. Therefore, it is necessary for you to avoid this bias as much as possible. The reason is that if felt, it can harm the readership of your research pretty well. So, resist the bias and do not give an analysis that feels like a personal perspective on the research topic.


Conclusively, analysis in academic research is difficult to perform. However, having an idea of the necessary things to avoid can be very helpful in the analysis. So, read the information above and avoid all the 7 things mentioned number-wise. If you do this, I guarantee you a perfectly analysed academic research.

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