BEing positive with negative results



An accurate representation of 20.109 so far:


I came into 20.109 with past students telling me it was the class they had benefitted the most from during their time at MIT. Everyone told me “It’s hard, but you’ll get through it, and it will so rewarding.”

And I can really relate to that right now. I think I spent more hours analyzing PPIase data last weekend that I did sleeping (I promise I get a normal amount of sleep most weekends). But when everything was done and I hit submit on Stellar, I felt like a champion. But like everyone who is in 109 knows, there’s something to do every night, so after a short break, I got to work on the next assignment.


Izumi and I started off MOD1 with high hopes. Our gel came out great, and we both had a relatively good idea with what was going on in all of the experiments…our perfect lab experience came crashing down when there was no FKBP12 band on our SDS-Page.


I think that the hardest part of the MOD1 data summary was to write a whole report on data that was not significant. I love having negative specific activity!!! I found it hard to write what I wanted to say in a concise way, but the Data Summary forced me to do just that. I also felt really overwhelmed when I started analyzing the PPIase data. I had never taken a statistics course, so I didn't understand the meaning of a p-value. It took me a long time to understand what I had to do to extract the data that was important for our experiments. 

How I felt at the beginning of data analysis:


How I feel now:


I also learned the importance of organization when writing up results. I felt really overwhelmed by all of the graphs and different T-scores and confidence intervals I had generated while trying to find something good about our data, even if it was just "trends". 

My feelings towards Excel during data analysis (it quit on me twice!!!):


It was hard come up with hypotheses as to why our results were not what we expected. I know that experiments that actually work in science are not very common, but all the papers that get written and published are about experiments that did work. However, I think that having to do this made me grow as a scientist because it made me have to understand what we did to see where things may have gone wrong.


During the mini presentation, I found it really hard to communicate everything we did in this module in under three minutes. I also found it really hard to film myself so that I didn’t blank on what I was saying or completely mess up what I was trying to convey. For next semester, I recommend the following (three minutes is plenty of time for a dance):














I have high hopes for Mod 2. Now that I actually know how to make figures in power point and have a grip on how to use excel, I think that analyzing data/making figures shouldn’t take me forever. Mod 1 taught me that I actually really like working in a lab and analyzing experiments. Even if it takes forever and experiments don't go as planned, I am excited to go back the next day and work on another experiment. I'm so happy to be a Course 20!

Despite all of the insignificant data, I still feel like I have learned a lot so far in 20.109. I’ve learned so much. Even though I have had a UROP since freshman fall, this class has taught me so much on the science behind everything we do. It's hard to think that we've been in this class for less than two months because I have learned so much. Even though I feel dead after spending 4 hours in lab on Tuesdays and Thursdays, I feel like I am learning valuable information every day that I will use in my career.


~Andrea




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