- Resources for R Programming
- References for R Programming
- Data Science Specialization Value Proposition
- R Onboarding for SAS Users
- Strategy for Coding the Programming Assignments
- Tutorial for those struggling with Programming Assignment 1
- Breaking Down pollutantmean
- Assignment 1: A More Elegant Solution
- A SAS Version of pollutantmean?
- Tutorial for those struggling with Programming Assignment 2
- Tutorial for those struggling with Programming Assignment 3
testthat, Unit Tests for Programming Assignment 1
testthat, Unit Tests for Programming Assignment 3
- Alternative submit script for Programming Assignment 1 that makes submitting more convenient by allowing selection of multiple parts plus prompting if user wants to submit another part before exiting
- Grading the SHA-1 Hash Code
- Assignment 2: Demystifying makeVector
- Assignment 2: makeCacheMatrix as an Object
- Some notes on the R Language
- A Data Frame is Also a List
- S Objects, R Objects, and Lexical Scoping
- Common R Mistakes: Overwriting Functions with Data Objects
- Forms of the Extract Operator
- Functions to Sort Data Frames
- Creative Use of R: Downloading Course Lectures Article illustrating how to use R to automate the download of lectures from Data Science Specialization courses, such as R Programming. Techniques used in this article are helpful to make research reproducible, as required for courses like Getting and Cleaning Data and Reproducible Research.
- Lexical Scoping and Statistical Computing Article by Robert Gentleman and Ross Ihaka at the University of Auckland describing how lexical scoping works, and why it is valuable in statistical computing.
- Data Science Job Report 2017: R Passes SAS, But Python Leaves Them Both Behind Bob Muenchen’s take on the job market for various data science langauges.
R language cheatsheet
R and Commercial Statistics Packages
- R Onboarding for SAS Users Provides an overview and links to a variety of resources to help people with SAS experience make the transition to R
- Commercial Statistics Packages: An Historical Perspective
- Why is R More Difficult than SAS?
- Thinking in R versus Thinking in SAS
- Complete notes for R Programming