Course overview

Welcome and organization

Veronica Codoni

University of Luxembourg

28 May 2024

Good morning!

What you can do now:

Check for material at the main site

https://r-training.pages.uni.lu/r-intro/

Install R, RStudio and packages

https://r-training.pages.uni.lu/r-intro/setup.html

Check your install

Overview

Learning objectives

This course provides an introduction to R basics and RStudio in an interactive manner.

This training prepares learners for working on projects in R with R Studio and provides essentials for performing more complex tasks such as those covered by Data processing with R Tidyverse and Statistical tests and statistical learning for omics data courses.

Content

  • R data structures

  • Basic transformations

  • Descriptive statistics

  • Basic plot capabilities

The course workload ~ 20 hours (1 ECTS) is composed of:

Lectures

  • Slides, formal lecture
  • Quick exercises inserted
  • Live demo

Practicals

1 ECTS

  • Written and practical exercises, R script files
  • All documents allowed
  • Internet allowed

Internet access allowed, watch out time

why allowed

Downside!

Time vanishes fast if you aren’t prepared!

Speaker & helpers

Veronica Codoni

  • Course design

  • Instructor

Roland Krause

  • Support

Time table

Day 1 - 2 - 3

Time
09:45 Set-up & questions
10:00 Course work - mix of lectures and exercises
13:00 Expected finish

Let the journey into R begin!

Credit: Artwork by Allison Horst

Demo live: Baby names over 137 years in US

Data set was provided by the USA social security administration gathered information on baby names in US for each year from 1880 to 2017. All names with more than 5 uses were included. (Source: http://www.ssa.gov/oact/babynames/limits.html)

The data set is part of babynames R package, developed by Hadley Wickham, and needs to be installed with install.packages("babynames")

Dataset

# Install the released version from CRAN
install.packages("babynames")
library(babynames)
babynames
# A tibble: 1,924,665 x 5
    year sex   name          n   prop
   <dbl> <chr> <chr>     <int>  <dbl>
 1  1880 F     Mary       7065 0.0724
 2  1880 F     Anna       2604 0.0267
 3  1880 F     Emma       2003 0.0205
 4  1880 F     Elizabeth  1939 0.0199
 5  1880 F     Minnie     1746 0.0179
 6  1880 F     Margaret   1578 0.0162
 7  1880 F     Ida        1472 0.0151
 8  1880 F     Alice      1414 0.0145
 9  1880 F     Bertha     1320 0.0135
10  1880 F     Sarah      1288 0.0132
# … with 1,924,655 more rows

Questions?

  • Number of babies born per year

  • Evolution of your first name

  • Comparison of popularity between names over the years

  • …

Install line must be commented out with a # to avoid running it at each knit compilation.