Data Analysis Cont.

It is unbelievable that the research period is just about over already! The past 8 weeks have flown by. However, progress with data analysis is slowing down. I have successfully cleaned all my insect data and calculated several diversity measures for each site and transect using R for Statistical Analysis. Using R was not as terribly daunting as I was anticipating though it was frustrating at times. The feeling of triumph when a code would finally work made the frustration well worth it! Altogether, I have calculated abundance, species richness, Simpson’s diversity index, Chao’s species estimator, Pielou’s evenness measure, and rarefaction curves for each data site. I am now working on turning my calculations into visuals. I can preliminarily judge the differing diversities of the sites, but will also be running statistical tests on the data to see which sites are overall “more diverse”.  I will obtain the patch sizes for each transect to complete my analysis.

Aside from finishing up analysis on my insect data, I am also going through my herbivory data and cleaning it up so it can be included in our overall milkweed project and so I can potentially use herbivory information to compare with diversity data. I am pleased with my partial triumph over R and with the data I have generated through calculations. I have learned so much about milkweed and the milkweed insect community and have had a blast with my lab group while doing so. It has been a great summer and I can’t wait to report about my findings!

Comments

  1. John Nguyen says:

    It’s incredible how fast the summer went. I was here a bit longer, for ten weeks, and it still seemed to just whistle by me.

    The previous semester, I wasn’t able to be as involved as I would’ve liked. I wasn’t familiar with what “data cleaning” (why is it dirty?) or “data coding” (do I need a computer science degree for this?) and now I almost wish I wasn’t so familiar with the painstaking hours of getting everything properly entered sorted so the data can be interpreted. It appears you’re in a biology lab, so I imagine it’s slightly different from my social cognition one, but I think the horror of statistical programs is a universal constant. If there’s one significant finding I’ve made this summer, it is that.

    But yes, it was always great just to get things to work! Especially if it was a simple mistake holding you back from glorious data. I remember one of the first times I ran an EEG study this summer, we were wondering why the program wasn’t lighting up green for the electrode nodes to indicate that we had reduced impedance and gotten good signal conductance. It turns out we had done everything right – we had just forgotten to hook up the electrode cap to the amplifier. Sometimes it’s the simple things.

    I remember seeing the terms that you’ve mentioned in my introduction biology course – species richness and abundance and such. It’s interesting to read about the actual process of data analysis that you have to do. It’s been great this summer to see how the stuff we learn is “prepared,” so to speak, before it is “served” to us in our classes.

    Good luck wrapping up your study.