Computer programming E140

Lecturer: Jonas Schöley (jschoeley@health.sdu.dk)

Preparation

Please install the current versions of

• R (https://cran.r-project.org/) and
• Rstudio (https://www.rstudio.com/products/rstudio/download/).

Course structure

• Mon Sep 11, 14-16: Basic R
  • Lecture code
  • Self study material
    • GDPe02012.txt, swed_kaza.txt
  • Should you prefer a more technical introduction to the basics of the R language (maybe if you are familiar with other programming languages) then I suggest to read the "Foundations" chapter of Advanced R.
  • Introduction to R Markdown
• Wed Sep 13, 10-12: Data structures
  • Lecture code
    • swe_dxnx.txt
  • Self study material
    • deathsAustria.txt, popAustria.txt
• Fri Sep 15, 10-12: Functions and control flow
  • Lecture code
  • Self study material (Flow control and functions)
    • lxJPNfem.txt, FertJPN.txt, GDPe02012.txt, deaDENf.txt, popDENf.txt, deaFRAf.txt, popFRAf.txt, deaITAf.txt, popITAf.txt, swed_kaza.txt, FunEgypt1997.txt, FunUSA1991.txt, USAfert1991.txt, USAfert1992.txt, USAfert2000.txt
• Mon Sep 18, 14-16: Data visualization
  • Lecture code
  • Self study material
  • How to do Lexis surfaces in ggplot?
• Tue Sep 19, 14-16: Data transformation
  • Lecture code
    • hmd_lt.RData
  • Self study material (data transformation)
  • Self study material (tidy data)
• Wed Sep 20, 14-16: Optimization and model fitting
  • Lecture code
    • hmd_lt.RData
  • Self study material
  • Cran task views are collections of R packages categorized by topic. The task views are a good place to get an overview of the packages available for a given problem domain.
• Thu Sep 21, 14-16: Probability distributions and simulation
  • Lecture code
  • Self study material
• Fri Sep 22, 14-16: Matrix Algebra
  • Lecture code
  • Self study material

Assignments

• Assignment 1 due Sunday, September 17.

  • Reference solution
  • FAQs concerning assignment 1

• Assignment 2 due Sunday, October 1.

Format

Please email me the finished assignments (jschoeley@health.sdu.dk). For each assignment I would like you to send me at least 2 files:

1. the source code (.R, or .Rmd), and
2. a pdf with your code, your comments, your results and your answers to the questions in the assignment.

If you have downloaded data for the assignment please send me this data as well.

If you need help

Of course you can and should take advantage of your peers when you're stuck. This does not mean to copy the solutions but instead to ask for help on specific problems. You can also send me a mail asking for advice. Make sure to attach your data and code to the email so I can have a look at what went wrong.

Grading

You get a pass if you hand in all of your assignments. There are 3 ways to get a high pass:

1. Do you assignments very well, i.e. maybe do a bit more than I've asked for.
2. Write down which problems you've encountered while working on the assignment and how you've solved them.
3. Hand in some special assignment that I've given you (that is for those who already know R).