So much Data

The most difficult part of this module was summarizing the results and emphasizing their importance. While data from each separate experiment was easy to explain as me and my partner began to tie them together, putting the pieces together became more difficult. Additionally sometimes data makes no sense, which isn't ideal when writing a data summary, thankfully the class data saved me and my partner. I enjoyed the fact that most of the results section was focused on the visual representation of data, it made comparing the data sets from our results easier. The student t test while annoying to calculate, did allow me to tell the reader that two separate data sets were significantly different. However once we finished analyzing all the data, telling the readers which data to look at when discussing our main points wasn't as clear. Which experiment best illustrates this point? Shouldn't we have done significance for the other conditions? were just a few of the many questions that crossed my mind when writing this data summary.


In the future I think it would be more useful to go over my hypothesis and methods before the working on my result section, in order to remind myself what type of data I expect to get and why that would prove my point.  Even reviewing the background/motivation section will allow me to see how other scientists tied their results together in order to show readers their results were significance. Finally I think it helps to check if you are trying to prove too much in your main takeaway, since a simple conclusion doesn't make your results any less significant.


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