Conclusions must be strong. This is the conclusion of this post talking about conclusions. I think this conclusion is strong enough!!
A stack of 30-50 conclusions organized in a good storyline
makes one research paper. Thus, having a strong conclusion in every experiment is
important.
What is a “strong” conclusion?
Then, what is a strong conclusion? Strong conclusions do NOT have to be good data or happy ending, but strong
conclusions have to be conclusive and exclusive.
 |
| dead end could be a strong conclusion |
Practice
Let’s start with your easiest data and have a conclusion drawing from the data. Then, list
10 ideas that deny your original conclusion. They can be stupid (like computer
virus hacked my PC and destroyed my data) or mere human
error. Can you disprove all of the denying ideas? If you think of some convincing
denying idea, can you conduct
another better-designed experiment? If you decide to switch the conclusion, then
do the same process until you are fully convinced by yourself. It is the definition of a strong conclusion.
Your
data should be convincing and beautiful (This is the definition of “data quality.”), but does not have to be something expected. Students sometimes scream "This is the bad result!" right after the experiment without the analysis, but research is not like that. As Issac Asimov said "The most exciting phrase to hear in science, the one that heralds new discoveries, is not 'Eureka!' but 'That's funny...'." So experiments can be funny. The point is that you focus on improving data quality, and draw a strong conclusion from the data.
Good luck on strongly concluding your experiment!
