Isis the Scientist had a post yesterday (with lots of discussion) about in what order the various sections of a lab report should be written. Whatever. People, do what you want, just make sure that the final product is good. To me, the most important part of writing a report occurs before you start experimenting: it's the the time when you make up the data.
Yes, make up the data. Believe it or not, this was something I learned to do as an undergraduate engineering student, and the professors actually encouraged it.
Hear me out. The junior level chemical engineering lab was a royal pain in the posterior. It was long, it involved larger pieces of equipment than any of us had ever worked with and we were given little guidance as to how to run it. Each week, the team would receive a memo written out as if it were something that your supervisor (in industry) might send your way - the overall objective was clear, but there was little guidance as to how to proceed. Days before the lab started, we had to look at the equipment, imagine how it would work and also figure out which equations we would use to analyze the data. We would then have to make a proposal to the prof as to what our plan was and what data we would collect.
Now while we all (thought we) understood the equations being used, the biggest challenge we faced was making sure that we collected all the data that we needed when we did finally got into the lab and used the equipment. If we didn't get the data at that time, we were up the proverbial tributary without a proper means of forward locomotion. We would not be given a chance to back into the lab and rerun anything (much like industrial situations, by the way). So the best way to avoid the problem was to make up some data before we got into the lab, and run some calculations with it to make sure that we had all that we needed.
This actually provided us with positive two outcomes: first, we could verify that we were going to be collecting all the data that we needed, and second, by making what we thought were realistic guesses for the variables (as opposed to random numbers), we were training ourselves to anticipate appropriate values. If the actual values were significantly different, then we were able to learn why out hunches were so far off.
It's still an approach that I use (mentally) to this day - think first about the all the data that you will need and how you will get it. You may not get the results you want, but you will be sure that you can stand by what you do have.
Just make sure that you don't confuse your made up numbers with the real data.
Wow, I think I'll try this the next time I get an opportunity. I'm a ChE undergrad and any tricks to prevent disasters (like not having the right data) is always useful.
Let me paraphrase:
"Here's some shit Isis wrote. Now, here's some completely unrelated shit."
And, yeah. People can write a paper in any order they want and few people give a fuck. But, when it's not good because the story evolved as it was written linearly, they'll come back. They always come back.
This is true. Engineers are encouraged to think through the outcomes first. Sometimes with biological models, though, this can get in the way and I've had to tell engineers (while trying not to laugh), that they might want to talk to the cells before imposing too much stringency on the projected outcome. Ah, open systems, the bane of engineers. :)
We had to pass physics labs in the college, the instruments were exceptionally crappy, in poor working order, and we were graded based on how close we got to the secret correct value. It was the very first lab and the the three old ladies who run the labs were convinced they were giving proper experimental rigor to green students of natural sciences. Instead they taught us how to cheat shamelessly (determine the desired result independently, then create the curve, introduce appropriate noise, position the datapoints around the curve etc. (they particularly loved how precise was my molecular weight determination by measuring vapor tension of a solution - I just run NMR and few other simple analytical tests on the sample to find out what was the sample compound)
It was so blatantly wrong way of doing experimental work that it has served to me as an antidote against fooling myself ever since - whenever I have the inclination to round up the number a bit or throw out he "outliers" to make the data come out better I immediately recall that intro physics lab.
Excellent post! I think you've encapsulated the mission of this blog and our challenge.
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