01.1 – Let’s talk about how to talk about statistics! Part one

The first couple chapters of the ISLR deal with vocabulary and underlying concepts. I’ve chosen to summarize them in a series of hopefully more engaging and descriptive posts that break the information down topically. If you come from a STEM background, all of this should be at least passingly familiar, if not outright dull. If you don’t have a STEM background, then bear with me, cause the topic material (pretty much from here on out) is going to be dry and sometimes full of strange symbols that will frighten and enrage and confuse you at first. Rest assured, they are not sinister – they are in fact mostly chosen arbitrarily or aesthetically. They are merely tools, and you are here to learn how to make them do your bidding.

I’ll include links that explain various things in more detail if you’re like me and consistently find yourself having anywhere from 30 to 100 browser tabs open at one time that you never really fully read through.  So if you’re ready to add to your tab count, or otherwise just want a brief overview of some important basic statistics concepts and vocabulary, then by all means, jump down the rabbit hole!

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Teaching Myself R via the ISLR

This will be the first of hopefully a long series of posts of me learning the R programming language by working through the examples in An Introduction to Statistical Learning“, which is free in PDF form. Before we get too deep into code and math, keep reading if you want a high level overview of Python (which I am mostly comfortable with) and R (which I know very little of).

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