Introduction to Computational and Data Sciences
Frontmatter
R session information
I Toolbox
1
Introduction
2
Slack
2.1
Getting started
2.1.1
Creating a Slack account
2.1.2
Slack policies
2.2
How to use Slack
2.2.1
Channels
2.2.2
Direct messages
2.2.3
How to ask (good) questions on Slack
3
GitHub
3.1
Getting started
3.1.1
Account sign-up
3.2
Navigating the GitHub site
3.2.1
Main dashboard
3.2.2
Profile page
3.2.3
Settings
3.2.4
Class organization page
3.3
Repositories
3.4
Additional topics
3.4.1
How to create a repository
3.4.2
How to import a repository
4
RStudio Server
4.1
Big picture overview of RStudio Server
4.1.1
RStudio
4.1.2
RStudio Server
4.1.3
Reference
4.2
A guided tour of RStudio Server’s default interface
4.2.1
RStudio Server sub-windows
4.2.2
File tab
4.2.3
Edit tab
4.2.4
Code tab
4.2.5
View tab
4.2.6
Plots tab
4.2.7
Session tab
4.2.8
Build tab
4.2.9
Debug tab
4.2.10
Proflie tab
4.2.11
Tools tab
4.2.12
Help tab
4.2.13
References
4.3
Help and documentation for R and RStudio Server
4.4
Initial Set-up
4.4.1
Change Global Options
4.4.2
Connecting RStudio to Github
4.5
Installing and updating R packages on RStudio Server
4.5.1
Option - 1 (Without commands)
4.5.2
Option - 2 (With commands)
4.6
Interacting with your files on RStudio Server
4.6.1
Setting path for the working directory
4.6.2
Creating a folder
4.6.3
Uploading a file
4.6.4
Deleting or renaming a file
4.6.5
Viewing a file
4.7
Creating a new file on RStudio Server
4.8
Using RStudio Server to clone a Github Repo as a new project
4.8.1
Step - 1
4.8.2
Step - 2
4.8.3
Step - 3
4.8.4
Step - 4
4.8.5
Step - 5
4.8.6
Step - 6
4.8.7
Step - 7
4.9
How to stage, commit, and push to Github using RStudio Server
4.9.1
Step - 1
4.9.2
Step - 2
4.9.3
Step - 3
4.9.4
Step - 4
4.9.5
Step - 5
4.9.6
Step - 6
4.10
Switching between Github repos in RStudio Server
4.10.1
Step - 1
4.10.2
Step - 2
4.11
Other common questions about RStudio Server
4.11.1
What happens if you close the browser tab?
4.11.2
I clicked “import dataset,” but I can’t find the file I downloaded, where is it?
II R Programming
5
Overview
6
R basics
6.1
Data
6.1.1
Numbers
6.2
Variables
6.3
More Complicated Data
6.4
Functions
III Readings
7
Describing numerical data
8
Representing distributions
8.1
Probability mass functions
8.1.1
Example dataset
8.1.2
PMFs
8.1.3
Plotting PMFs
8.2
Cumulative distribution functions
8.2.1
The limits of probability mass functions
8.2.2
Percentiles
8.2.3
CDFs
8.2.4
Representing CDFs
8.2.5
Comparing CDFs
8.3
Credits
9
Statistical inference with infer
9.1
Case study: Comparing work travel times
9.1.1
Work travel times in Iowa and Nebraska
9.1.2
Defining the hypothesis test
9.1.3
Building the null distribution
9.1.4
Computing the two-sided p-value
9.1.5
Computing the 95% confidence interval
References
Published with bookdown
Introduction to Computational and Data Sciences
Chapter 5
Overview
The following chapters will introduce you to the basics of the R programming language.