And just like that, Summer B is over and I've acquired some new statistical methods and processes.

This was the first time I've taken only one class during an academic semester, and it was nice to be able to devote my whole attention to the class, immersing myself in homework for a few hours without having to think too hard about time management with other workloads.

The underlying assumption of nonparametrics is that the population from which we have gathered data is non-normal, therefore we use specified ranking procedures to normalize the data. While it is true that nonparametrics statistical tests tend to reject the null hypotheses on a wider interval than parametric tests, nonparametrics open up the doors to more accurately testing non-normal data.

The use of R (via R studio) was one of my favorite parts of this class. Even though we really only used R as a glorified calculator and didn't do any algorithmic work with it, the use of R gave me inspiration and insight on just how I might go about collecting and analyzing data on my own. The bulk of the work in R we did roughly followed this flow

- Input list of data
- Run test in R using this data (R does tedious ranking work for you)
- Compare test statistic to rejection region found in R

While we did use the R tests, oftentimes we would only do step 3 after we calculated the test statistic by hand. Moreso in this class than other stat classes, I was able to see the beauty in the equations. The use of R tests paired with the handwritten work provided me with more insight into what the tests were actually doing without bogging me down in tedious summations (for the most part).

This class gave me a better perspective on statistics, data science, and the art of learning in general. I feel that my learning mechanisms become more refined only if I'm actively learning, and this class forced me to do that for six weeks straight.

I got a 100% on the final exam and finished the class with an A (95%)! I'm looking forward to taking Computer Science 1, Security in Computing, Computer Logic and Organization, and statistical methods 3 in the fall.

I was inspired to tune-up the website today a bit after reading a bit of Peter Siebel's *Coders At Work*, and specifically his interview with Brad Fitzgerald, founder of LiveJournal. The motivation, technicality, and workflow described in this book is truly inspirational for me. Fitzgerald describes his troubles with apache and mod_wsgi, and then he explains all of these workarounds and his team had to make when LiveJournal's data outgrew the original database. It's comforting to know that these powerhouse programmers have ran into some of the same problems that I have encountered.

I will continue to read *Coders At Work*, as well as J. A. Baker's *The Peregrine*. I've rediscovered the joy of leisurely reading, and hope to take that with me into this fall semester.

Until next time,

**Brett**