Basic statistics in R, Leuven - online

Basic statistics in R, Leuven - online

Location:

online

Start date:

28 May 2020

Duration:
28 May 2020
12 June 2020
18 June 2020

General context

The training will be replaced by a set of online sessions.

Please register if you want to be notified of the details of the online training.

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This training gives an introduction to the use of the statistical software language R. R is a language for data analysis and graphics. This introduction to R is aimed at beginners. The training covers data handling, graphics, and basic statistical techniques. 
R is for free and for more information you can visit the CRAN web site.
This training is an introduction to the use of R and RStudio and stops at very basic analyses (t-tests and non-parametric equivalents). A full overview of statistical analyses in R including regression, ANOVA will be given in the follow-up training Basic statistics in R, part II.

Objectives
  • Get an idea of what R and Rstudio is
  • Use R to handle data: creating, reading, reformatting and writing data
  • Use R to create graphics
  • Use basic statistical techniques in R : normality tests, t-tests, wilcoxon tests, chi square tests, correlations, survival analysis...
  • Write and use R scripts
Event intended for

This training is recommended for people with no experience in R who are planning to follow a training that requires some R background, like the mass spectrometry training, the single cell RNA-Seq and the bulk RNA-Seq training....

Required skills

The training is intended for people who have no experience with R. However, understanding of basic statistical concepts is required, such as data types, normal distribution, descriptive statistics, tests for comparing groups... If you don't have sufficient statistical background you are strongly encouraged to attend the Basic statistics theory training. 

Course materials

Trainers

Janick Mathys

VIB Bioinformatics Core training coordinator

Contact Janick Mathys :

Program

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Introduction

Working with R and RStudio

Data structures

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Data structures

Reading data from files

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Writing scripts

Descriptive statistics

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Data reformatting

Graphics

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Graphics

Basic statistical tests

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Full analysis of data sets