Nt1310 Lab 2

Trenton Mackey-Section BD

When people think of scientists, creativity is not always the first thing that comes to mind. Scientists are viewed as quite the opposite in fact, relying on cold, hard facts, rather than having the mind to create a colorful, bright work of art. However, nothing could be further from the truth. Scientists employ a great degree of creativity when drawing diagrams of observations, thinking of new ideas, and interpreting data in unique ways. Of course, all of the above is limited by the facts, for example you can’t just draw three extra legs on an animal because you want to be creative. However not all scientist’s drawings are going to look exactly alike because everybody is a different person. No two scientific papers are going to be the exact same either, in fact they could in fact be near complete opposites, depending on how one scientist

chooses to interpret the data.

As long as all the facts are there, both papers could be just as legitimate. In Lab #6, we got creative ourselves. Everyone was tasked with diagramming a centipede and a millipede. We all looked through a microscope at both organisms. In my group there were three of us, all looking at the exact same centipede and the exact same millipede. However, all of our drawings looked very unique. It was apparent that I was less of an artist, thus my drawings looked a lot worse, however this exemplifies our creativity in that each of us made a unique drawing. Another example was in the first lab we did, Lab #2. The general consensus of the class was to interpret the data to not support the hypothesis, however a few used the data to support it. This shows creativity in that different people had different opinions on the same data, and formed different, but still

valid conclusions about it.
Another aspect of science, that also kind of ties into this that science is data driven, but also inferential. What this means is that the data is fact, and you cannot go against the facts, but you can choose to interpret the data in a variety of ways. As long as the inference of the data is consistent with the evidence and data shown, it can be seen as valid. For example, if you observe a butterfly that can’t fly well in the cold, you could interpret your observation as butterflies cannot fly well in the cold. Of course, this can’t be proven, but only supported, and in this case it would be a good idea to gather lots more data, as it could be possible some other factor is causing the butterfly not to fly well. In our Lab #2, again we all had the same exact data as a class. However, we all had a unique lab report and a different interpretation of the data, even though the data was the same. Not a single one of our lab reports, provided our conclusions make sense in terms of the evidence provided, could be seen as illegitimate. Another example was the very next lab, Lab #3. In this one, we all had to come up with our own hypothesis, and prediction of that hypothesis, however the data collection remained the same as a class. Once again however, all of our lab reports were very different, but still very legitimate. Different people are always going to interpret data a different way.