A Guide to Writing Data Analysis and Findings in a Research

Data Analysis and Findings

Reporting your findings is a huge part of your research. It is what makes up the bulk of your research as well as what the majority of your research viewers want to see; not your introduction, analysis, or abstract but your findings and the data gathered.

These must be presented in a fashion that is understandable by your readers. They are reading your report because they want to know what exactly you have found out that is new. Presenting your data and findings in the best way is exactly how you answer their questions.

Want to write a succinct data analysis and findings in your research? Follow the steps below

Screen Data Collected

Usually, during research, you come across a lot of fascinating data and information on your research topic and on other areas relating to it. You need to screen the data and findings you have gathered to decide exactly which of them is needed in your research. How? You can decide to divide them in a tabular form; using headings relative to your project topic.

At the end of your division, look at the ones that fall under topics related to your research and note them. Then, the ones that do not fall under the headings related to your research will have to go. You can decide to keep this information for future purposes (you never know when you are going to need them) but for now, do not add them to your project.

Why? Once you start adding information that is not necessary or an answer to the original question you set out to answer through your research, you start rambling. Your work looks like one that lacks direction, confusing your readers and causing them to be distracted from the real issue at hand that your research hopes to tackle. By the time they are done reading the important information and the less important ones, they would not understand you. A bunch of information is good but, a bunch of needed information is better.

How to Determine the Type of Data

In research, there are two basic types of research data; qualitative and quantitative data. Qualitative data is non-numerical and presented in the form of words while Quantitative data is numerical and very quantifiable. Both are very important in research and complement each other, to bring home your point leaving no doubt in the mind of your readers.

You can see from these two types that they vary so in turn, how you present them should vary. For the most part, reporting methods for these two types interchange and these are reported together, not separately, because most of the time, the information they present go hand in hand. Reporting them involves the use of:

Subheadings: Qualitative data is usually presented in words as we have earlier mentioned. Gotten from the review of other resource materials and interviews, it tends to be bulky, and sometimes writers find it difficult to present it in a way that does not overwhelm their readers.

When you decide to report your findings using subheadings, it is best to first draw up a plan; find the similarities between all the data and findings gathered and group them accordingly. Next, present your data in this grouped form, usually by use of similar themes that they share as subheadings.

This way, the information is divided into smaller chunks; making it easier to understand and is not overwhelming for your readers. Just ensure you group them according to a theme so, when the qualitative data is presented, quantitative data is also there to buttress the point. This way, your readers have a sense of direction as to where your research paper is headed.

Use of Examples: This might seem trivial or not important but it is. Sometimes, the data is too hard to comprehend or more sophisticated than expected. Examples are a simpler way of explaining your findings are data. It makes what you are trying to explain more relatable, gives more relatable scenarios, makes your research easier to understand and links it back to the original research question.

Graphics, Charts, and Tables: This is usually prescribed for quantitative data. This data comes in a numerical form so, classifying it using tables and charts is way easier. Analyze and arrange the data according to importance as well as relevance to the particular subheading you are putting them under. These will have to go hand in hand with qualitative data as well. The use of graphs will help explain progressions as well as differences that exist and make it easier to compare variables.

Use of comments: These are used mainly for quantitative data presentation. It is not enough to just put the data in graphs and tables, an explanation has to follow. These explanations you usually see under tables and graphs saying something like ‘fig1.2 shows…’ are what we call comments. They offer more information on the data presented, breaking it further down for readers to understand.

No matter what type of data and research findings you are reporting, it is important to always link it back to the question your research hopes to answer or what it plans to explore. Presenting data and findings in a standalone way tends to leave readers confused as to how what you are presenting relates to the question of your research.

This is why screening data gathered is important to avoid using unrelated data and presenting your findings using a well-defined structure to enable easy comprehension and support understanding when reading.