Pitfalls in Data Analysis: Ways of Avoiding

Even the slightest mistake in your analysis can damage the quality result of the research that you conduct. If you carefully go through every stage of research, then the common pitfalls can smartly be avoided. Here, is what you need to do to ensure so.

While preparing a hypothesis you are more concerned about the data pattern to follow, rather than concentrating upon the details of the data. After all, the data has to be right, else your research will get scrapped. Therefore, you should never approach the idea of data analysis without having any specific outcome planned out. Verify the analysis from somebody else who can justify your results by giving an opposing perspective in this regard.

Give a second read to the results and cross-check them. You will definitely come across certain data that is not pertinent to the study. Try to evade such distraction since it can cost you a lot of energy and valuable time without fetching any desired results. Mark the perimeters for the data analysis so that you are ensured of the final results.

Check out for correlation and causation. This means that you might confuse between the meaning of correlation and situation. For instance, an action might trigger another; and so in that case both are related. However, two things may occur at the same time, but there might not be any correlation between both. The right way to combat the situation is by proving it null. In that case, eliminate the particular variable causing confusion.

Ensure that you get the right size of data. This means that if you implement small data sets, it helps you compare the results. In this manner, you can derive an error-free statistical significance.

Thus, be aware of the common pitfalls that you might come across in data analysis. Imply the best data analysis methods and overcome the problem.

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