An introduction to R, WS 2016/2017

Title: An introduction to R

Instructors: Dr. Noémie Becker, Dr. Benedikt Holtmann, 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 2016/17: February 27, 2017 till March 10, 2017
Room: G 00.001 Exceptions March 6 in B00.019 and March 9 in B01.027
Time: 9:00-12:00
The afternoons are for preparing the exercises in rooms C00.005, G00.037 or D00.021.

Exam:
The final exam will be on March 10 at 10:00 am in lecture room B00.019.
The make-up exam will be on April 3 at 09:00 am (room B01.019).
To take the make-up exam you need to register by e-mail to Noémie Becker 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)
Grades for the exam: Grades
If you don´t remember your exam number, send us an email.

Material:

The course syllabus can be downloaded here: Syllabus

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]
  Script: [Day2_script.R]
  Additional files: [Day2_example.R] [woodpecker.txt]
• Lecture 3: Data types and structures
  Slides: [pdf]
  Script: [Day3_script.R]
• Lecture 4: Data types and structure (continued)
  Slides: [pdf]
  Script: [Day4_script.R]
  Additional files: [Snail_feeding.csv]
• Lecture 5: Algorithmics in R
  Slides: [pdf]
  Script: [Day5_script.R]
  Additional files: [lifespan.csv] [lifespan2.txt] [lifespan3.txt]
• Lecture 6: Algorithmics in R (continued)
  Slides: [pdf]
  Script: [Day6_script.R]
• Lecture 7: Data manipulation
  Slides: [pdf]
  Script: [Day7_script.R]
  Additional files: [Fish_survey.csv] [Water_data.csv] [GPS_data.csv] [Fish_survey_long.csv] [Bird_Behaviour.csv]
• Lecture 8: Data visualisation and graphics
  Slides: [pdf]
  Script: [Day8_script.R]
  Additional files: [Sparrows_2.csv]
• 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]
• Sheet 3 [pdf]
  Solution: [R]
• Sheet 4 [pdf]
  Files: [Sparrows.csv]
  Solution: [R]
• Sheet 5 [pdf]
  Files: [heartbeats.txt] [birdnests.txt]
  Solution: [R]
• Sheet 6 [pdf]
  Solution: [R]
• Sheet 7 [pdf]
  Files: [Catfish.csv] [Treatment.csv]
  Solution: [R]
• Sheet 8 [pdf]
  Files: [Catfish_2.csv]
  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 nbecker-at-bio.lmu.de.