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Data Analysis

Data Analysis

What is Data Analysis

Data analysis is the thorough and careful viewing and interpretation of data collected through an investigation. The data analysis then reveals results with which the research questions can be answered correctly. Data analysis takes place in both qualitative and quantitative research.

When conducting research, it is of course all about collecting data, so that certain insights are then obtained based on this data. The answers people give to the questions contain that little bit of information that is needed to answer important questions.

So far it is all clear and clear, but what can you do or not do at a data analysis? In the first place, it is very important to look at the collected data completely independently and not to focus on finding confirmation of assumptions made. With much research, it is true that based on your own intuition or available knowledge, you have already figured out what the answer to a research question might be. The big danger then is that the data only searches for information that confirms the previously formulated answer. And that is very dangerous, since it leads to bias and therefore to incorrect conclusions and answers.

When you conduct qualitative research, you will have a lot of text to work out and go through. This text is the result of open interviews, group discussions or another form of qualitative research. In this data you then look for the deeper story behind your research question. You will not be able to use generally applicable judgments, but the data will provide useful insights and make an important contribution to the possible why of a problem or question. In most cases a research report or report consists of interview reports, minutes written during group discussions and of course conclusions and possible recommendations.

When you carry out quantitative research, you actually start working with large amounts of data. Mainly closed questions were asked and you usually analyze these by making tables and graphs. You do this for example by crossing two different variables (questions from your research). For example, you gain insight into differences between men and women or between young and old. It can also be examined to what extent those differences between certain groups are significant or not. The results from such analyzes are delivered in an online dashboard or an actual report in, for example, PowerPoint or Word.
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