Summarize

I found this awesome slide deck from Jake VanderPlas. This follows a concept that took me many years to finally understand and even longer to identify. The field of Mathematics is simply a system of codified syntax for unambiguously expressing structure, just like all programming languages. However unlike programming languages the syntax and structure of Mathematics is resistant to change;

Once you understand (and agree with) this basic concept, Mathematics becomes much less scary and it becomes a task of understanding the syntax and structure. The way I find this most easy to understand is to express complex mathematics as simply programming structures (note, I am not saying all complex math can be represented in this way, some of this shit is just hard). Then when I encounter the formal notation I think to myself 'oh thats just a loop'.

Jake explains this approach better than I can;

The field of statistics has a reputation for being difficult to crack: it revolves around a seemingly endless jargon of distributions, test statistics, confidence intervals, p-values, and more, with each concept subject to its own subtle assumptions. But it doesn't have to be this way: today we have access to computers that Neyman and Pearson could only dream of, and many of the conceptual challenges in the field can be overcome through judicious use of these CPU cycles. In this talk I'll discuss how you can use your coding skills to "hack statistics" – to replace some of the theory and jargon with intuitive computational approaches such as sampling, shuffling, cross-validation, and Bayesian methods – and show that with a grasp of just a few fundamental concepts, if you can write a for-loop you can do statistical analysis.

Check out the slide deck here