An introduction to R, WS 2017/2018

Title: An introduction to R

Instructors: Dr. Noémie Becker, Dr. Sonja Grath, Prof. Dirk Metzler

Contents: R is a widely used tool for analysing data in biology. Therefore it is important to learn it. R is a free statistics software and can be downloaded from www.r-project.org. In the lecture students learn the necessary theoretical background for using R. They will become familiar with the basic data structures and control flows of the R programming language. In the tutorial, the students become familiar with R, by first trying simple commands and then learning to perform basic data analyses and to write simple program scripts.

Time: Winter semester 2017/18: March 5, 2018 till March 16, 2018
Room: B 00.019 Time: 9:00-12:00
The afternoons are for preparing the exercises in rooms C00.005, G00.037 or D00.009.

Exam:
The final exam will be on March 16 at 10:00 am in room B00.019.
The exam results can be downloaded here: Results
The exam viewing takes place on March 23 from 10:00 to 10:30 in B01.015.

The make-up exam will be on April 6 at 10:00 am in room G00.001.
The make-up exam results can be downloaded here: Results

To take the make-up exam you need to register by e-mail to Sonja Grath before March 25.

For both exams, you will have 90 minutes to answer the questions. Participants can bring their personal assortment of formulas or notes on an A4 sheet. This A4 can have any contents on both sides BUT ONLY IN YOUR OWN HANDWRITING! (no copy, not print-out, not another person's handwriting)

Material:

The course syllabus can be downloaded here: Syllabus


The handouts may contain only a summary of the contents of the slides shown in the lecture. More detailed explanations are given on the whiteboard and with practical demonstrations during the lectures. The questions in the exam refer to the whole content of the course including lectures and exercises.

Lectures:  

• Lecture 1: Basic Algorithmics
  Slides: [pdf]
  Additional files: Chapter 1 - R in Action, R.I. Kabacoff (2015)
• Lecture 2: Getting started with R
  Slides: [pdf]
  Additional files: [Example.R] [woodpecker.txt]
• Lecture 3: Data types and structures
  Slides: [pdf] updated
• Lecture 4: Reading and writing data
  Slides: [pdf]
  Additional files: [Snail_feeding.csv]
• Lecture 5: Rearranging and manipulating data
  Slides: [pdf]
  Additional files: [Bird_Behaviour.csv] [Fish_survey.csv] [GPS_data.csv] [Water_data.csv]
• Lecture 6: Data visualization and graphics
  Slides: [pdf] updated
  Additional files: Chapter 11 - R in Action, R.I. Kabacoff (2015) Chapter 23 - R in Action, R.I. Kabacoff (2015)
• Lecture 7: Algorithmics in R
  Slides: [pdf]
  Script: [Day7_script.R]
  Additional files: [lifespan.csv] [lifespan2.txt] [lifespan3.txt]
• Lecture 8: Algorithmics in R (continued)
  Slides: [pdf] updated
  Script: [Day8_script.R]
• Lecture 9: Basic statistics with R
  Slides: [pdf]
  Script: [Day9_script.R]
  Additional files: [mars.txt]

• Sheet 1 [pdf]
  Solution: [pdf]
• Sheet 2 [pdf]
  Solution: [R script] [R markdown] [pdf]
• Sheet 3 [pdf]
  Solution: [R] [R markdown] [pdf]
• Sheet 4 [pdf]
  Files: [Sparrows.csv]
  Solution: [R]
• Sheet 5 [pdf]
  Files: [Catfish.csv] [Treatment.csv]
  Solution: [R]
• Sheet 6 [pdf]
  Files: [Catfish_2.csv]
  Solution: [R]
• Sheet 7 [pdf]
  Files: [heartbeats.txt] [birdnests.txt]
  Solution: [R] updated
• Sheet 8 [pdf]
  Solution: [R]
• Sheet 9 [pdf]
  Files: [ccrt.txt] [mite.txt]
  Solution: [R]

Links:

• Download R from http://www.r-project.org.
• Introduction to R from R-Projekt webpage www.r-project.org
• Reference card of R commands

Requirements: Basic understanding of statistics will be helpful.

Language English

LSF-Link An introduction to R (Lecture with exercises) (English)

Questions Please send any questions to grath-at-bio.lmu.de.