Precourse information

There are few things to do before the course starts. These include:

• Pre-course homework
• Setting-up environment
• Setting-up communication
• What to bring

Pre-course homework

• Biostatistics and machine learning is based on mathematics so in order to have a good start at the course we need to revise or pick-up the basics.
• Go to https://nbisweden.github.io/workshop-mlbiostatistics/session-precourse-math/docs and have a look at the Mathematical Foundations, 7 chapters covering basics of mathematical notations, sets, functions, differentiation, integration, vectors and matrices.
• Find pen and paper and write down the solutions (or your best attempt) to the following exercises:
  • Ex. 1.3: f, g, h
  • Ex. 1.4: e, f, g, h
  • Ex. 2.2
  • Ex. 3.2, 3.3
  • Ex. 4.6: h, i, j
  • Ex. 5.1: i, j
  • Ex. 6.1: e
  • Ex. 7.1: h

R, R-Studio and R Markdown

During the course we will be using R programming language within RStudio Desktop editor. We will be writing scripts using R Markdown (.Rmd). We will try to keep coding as simple as possible, but we do assume that you have a basic understanding of R and your computer setup with RStudio and R version 3.5.0 or higher.

R skills that will be useful during the course are:

• using R as calculator incl. raising values to a power
• being able to work with vectors and matrices, incl. subsetting and matrices multiplication
• reading in data from .csv files, e.g. with read.delim()
• printing top few rows or last few rows, e.g. with head() and tail()
• using in-built summary functions such as sum(), min() or max()
• being able to use documentation pages for R functions, e.g. with help() or ?()
• using if else statements, writing simple loops and functions.
• making simple scatter plots of one numerical variable against another, both with plot() and ggplot()
• being able to install CRAN packages e.g. with install.packages()
• being familiar with R Markdown format

Some tips on installing and using R, R-Studio and R Markdown under precourse-env.

R packages

Some additional R packages requiring installation that we will be using during the course are listed under precourse-env-packages

Setting up communication

• Check the Canvas website for event-specific details.

What to bring (have)

• a laptop with R and R-Studio installations (see below)
• solutions (or attempts) to the exercises (see above precourse homework)
• a working web camera and a quiet space to take the course from (if online)