18 January 2018

Hadley R [update]

Previously mentioned, "R for Data Science" is useful reference for the WickhamWay of doing R. I've been reading in a desultory way since receiving it, thus came across this bit on p. 291 "Vectors":
I think it's better to start with tibbles because they're immediately useful, and then work your way down to the underlying components.

Yes!!! Finally, An Important Person who takes my view! R is, first and foremost, a Stat Pack Command Language. 99.44% of R users just want to get some study done with Existing Machinery. Yes! Which, not to put too fine a point on it, is why so many have difficulty with math and stat in school: the curriculum is set up to build a "solid foundation" before teaching anything the student, in a later academic/professional venue, will use. By the time that stuff comes around on the guitar, the "solid foundation" has devolved to mush in the lower brain stem. Fact is, most of the angst in learning later math/stat comes from having forgotten Algebra I/II in high school.
[update]
An easy-to-read guide to sharpening math skills for those who have taken mathematics and elementary algebra in high school or college and find they need to brush up on these skills for use in their professional or personal life. Examples and problems are related to real-life situations.

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