preface
the role of the liberal arts in data science
some features of the text
the book is for you
Introduction
1
what is “data science for the liberal arts?”
1.1
the incompleteness of the data science Venn diagram
1.1.1
additional domains
1.1.2
an additional dimension
1.2
Google and the liberal arts
1.3
TMI
1.4
discussion: what are your objectives in data science?
2
getting started
2.1
are you already a programmer and statistician?
2.2
spreadsheets - some best practices
2.3
setting up your machine: some basic tools
2.4
a (modified) 15-minute rule
2.5
installing R and RStudio desktop
3
what R stands for …
3.1
some key characteristics of R
3.1.1
base R and packages
3.2
cha-cha-cha-changes
3.3
some technical characteristics
3.4
finding help
3.5
Wickham and R for Data Science 2e
4
exploring R world
4.1
go to the movies
4.2
go into the clouds
4.3
open the box
4.4
go to (data)camp
4.5
learn to knit
4.6
older approaches
4.6.1
using Swirl
4.6.2
reading/watching Roger Peng’s text and/or videos
References
Data science for the liberal arts
References