Day 1
If your research involves any data, it likely also involves:
This means lots of code.
We can borrow some ideas from software development to
At a bare minimum, we want our code to be:
Nice to have, but not absolutely necessary
Through automated testing
Work through a problem together, learn tools and strategies
= “I need help!”
= “Good to go!”
No sticky = still working
Share solutions/questions/responses on padlet:
https://padlet.com/sachsmc/rprogs23
Course website:
https://sachsmc.github.io/r-programming/
tidyverse
vs data.table
, we will focus on learning the general principles.
To get credit for the course, you must hand in and pass the exam which will be an email sent to michael.sachs@sund.ku.dk no later than 23.59 on April 4.
It must contain as attachments:
The body of the email should be the “readme” file, with details on
An easy way to do this is to do the exercises and save them all in a single Rmarkdown or Quarto document.
The week after the course and before April 4, I will hold office hours where you can come ask questions and get help on any R topic
I will send sign up link by email