# Linear regression with R

The aim of this course is to teach you how to analyse your data
using simple linear models.
We focus on linear regression in order to improve your generic statistics knowledge.
**Please note that we cannot go into the specific data analysis problems of your particular project.**

**Instructor:** András Aszódi.

## Topics

- How to fit straight lines? Single and multivariate linear regression.
- How to simplify the models? LASSO, Ridge, Elastic Net regressions.
- What to do with correlated independent variables? Principal component regression, orthogonal polynomial regression.

## Out of scope

This course will not teach you bioinformatics.
In particular, *no high-throughput sequencing data will be used* because they are impractically large,
and not everyone on campus is working with sequencing.

## Prerequisites

Participants should have a good understanding of basic statistics. Our Statistics with R course helps you refresh your stats skills.

Basic familiarity with R is advantageous, in particular:

- Using the R Studio environment
- How to invoke R functions, pass optional/named parameters
- Some familiarity with simple plotting commands

If you have attended our R as a programming language training then you are well equipped to take this course, but this is not a strict pre-requisite.

## Practical information

**Number of participants:** minimum 5, maximum 10.

**Length:** The course takes one half-day,
from 09:00 to 13:00 with 2 breaks.