Conclusions Archives - How to Write a Thesis

Are there any research questions criteria for your thesis? Well, your conclusion should clearly answer the research questions. It should provide a good background picture of your problem, what research questions were asked, and what findings lead to your conclusion. This chapter can be written once. In fact, I advise you to write it all once so you have a complete conclusion to your study. If you split it, you may start to repeat yourself, and start to bring outside topics into your conclusion.

Your written conclusion should be the culmination of your research journey. Some students are tempted to include conclusions not supported by the research findings. Therefore, the best way to do the conclusion is to follow the organization of your findings. Conclude every finding you have in Chapter 4. When writing your conclusion, keep in mind that professionals in your industry will only read your conclusion. Therefore, try to keep it simple, relative and to the point. You want to make sure your conclusions are supported by your data first and then supported by the literature. Make sure to be precise about your conclusions as they reflect your findings. You do not want misinterpretations of your conclusions that your findings do not support.

Stay away from definitive statements. Show modesty in your findings that articulate the study limitations. For example, if you say in your conclusion, “This research study proves that…,” then you are bragging about your study and asserting you have definitely proved your conclusions. This attitude may close doors for future research that may support your conclusions, and open doors to research showing your study had limitations, making it less than 100% accurate.

I remember Dr. Johnson who acted as a committee member for my doctorate degree. He reminded me that people believed the sun orbits the earth for a long time and insisted they had proof until Galileo came in and challenged this “fact.”

In short, use the terms: “the findings of the study seem to indicate …”, and those similar. This will give an indication that your findings also include limitations. You may have overwhelming support for your hypothesis, but your data is unlikely to prove it because future data set can always prove it wrong.

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So what is this causation correlation confusion?

When it rains, you get wet. When it does not rain, you do not get wet. Every time it rains, you get wet. Of course, while you are under the skies. This is causation. You can see the logic that if every time X happens, then Y has to happen. If any time X did not happen, we never see Y.

Correlation, on the other hand, is the fact that Y and X get together. It does not necessarily mean one affects the other. Rather, a third factor, such as Z influences them both. For example, you might get wet, and you might see the rainbow. These two correlate but they do not cause each other. The rain could cause both to happen, yet rain falls and then cease after some time, likewise the rainbow, it’s clearly seen in the sky after it rains.

It is important to distinguish between the causation relationship and the correlation relationship. You have to be very specific when you use this terminology because its meaning is very different.

For example, as people get jobs their happiness is raised. A research may reach this conclusion after surveying people about their work status, and their happiness level. A relationship can be measured using correlation analysis. Now, the correlation analysis may show a significant association between these two variables. Yet, we cannot claim that because people have jobs, they are happy. Even though, it makes sense that when people have a job, their happiness increases. The causation conclusion would require much work to prove, yet correlation can be sufficient to confirm your point, which says there is association between having a job and one’s happiness.