Things they didn’t teach in school

My gripe about graduate school is that the school focused on well-established software and never embraced nor encouraged open-source software. If they had taught, or at least introduced, these following open-source software, it would have helped us immensely to produce the best looking reports with great data analysis. We, however, had to struggle with SAS/Excel to get the graphs and analysis needed, and then spend hours to perform formatting in Word. Why they didn’t teach us:

  1. LaTex: a powerful typeset editor, where you focus on writing and not on formatting. It takes care of all the headings, page numbering, figure/table/equation numbering, TOC, bibliography/citation, and more. Although the learning curve is rather steep, once you get the hang of it, life becomes so easy. For windows: you need to get MikTex and any LaTex editor, such as LEd, LyX, or WinEd
  2. R: awesome statistical package with wonderful graphics components. Producing stunning graphics and statistics has never been easy. It had me at summary. Any software that can do produce the following, just by giving summary(iris) command has to be great:
Summary produced by R of the iris data set

Summary produced by R of the iris data set

In my thesis, I had plenty of equations, and every time I made some significant changes, MS Word happily would turn those equations into empty white boxes — and then I had to rewrite them. In retrospect, I find it ridiculous that I was entering citations manually. So every time I added a new reference, I would manually change the bibliography page and the page where I cited that reference. With LaTex, it is just a breeze to do all this.

Descriptive stats, Box-plots, normal curves, neural network, charts with LaTex equations, and a lot of more stuff, all could be easily done using R, and the best part is “repeatability.” With simple commands, you could export all the charts as images for various data sets or for various training algorithms. No sweat! Try that with Excel. (I did some years ago).

About the Author

A co-author of Data Science for Fundraising, an award winning keynote speaker, Ashutosh R. Nandeshwar is one of the few analytics professionals in the higher education industry who has developed analytical solutions for all stages of the student life cycle (from recruitment to giving). He enjoys speaking about the power of data, as well as ranting about data professionals who chase after “interesting” things. He earned his PhD/MS from West Virginia University and his BEng from Nagpur University, all in industrial engineering. Currently, he is leading the data science, reporting, and prospect development efforts at the University of Southern California.