Introduction to Data Science with R and R Studio (online)

To be announced

Scope

The aim of this course is to provide an introduction to data science, using R and R Studio. Participants will be introduced to R language syntax, enabling them to write their own R code. Participants will learn about R data-types and data-structures, and they will be taught how to explore data and produce plots. Finally we will showcase how to use R for analyzing experimental data using simple statistical techniques like t-tests, analysis of variance and linear regression. The focus is on the application of the techniques with R, and not the underlying statistical theory behind them. This is the first module in a series or courses in Data Science with R, covering many different subjects, from cleaning up datasets to creating interactive and reproducible reports with transferable skills that would apply to any scientific or business domain. The course will be a combination of lectures and practicals.

Learning Outcomes

• Getting familiar with the R language environment.
• Introduce participants to R Studio, an advanced environment for using the R language (scripts, projects, customizing R studio)
• Participants will get to know the R language syntax, how to write proper code for solving a given problem. They will learn how to work with variables to store data, and how to apply functions to data.
• Participants will obtain a strong foundation on the R data-types and data-structures (vectors, matrices, lists, data.frames) and how to properly work with them (access data, modify, filter). A good foundation of R data structures is very important for progressing in R for Data Science.
• Participants will learn the plot functions with base R, e.g. scatter plots, bar plots, box plots, histograms. They will learn how to use plot functions for exploratory data analysis (outliers, correlations, missing data). Participants will also learn how to customize plots (labels,colors, legends,  margins) and export them for publications.
• Participants will learn how to apply the most basic statistical techniques for experimental data, including t-tests, analysis of variance and linearregression.
• Participants will learn how to import and export data and will get to know the test datasets that R provides for practicing their skills.
• Participants will learn how to get help from the R help system and documentation. They will be able to deal with many common errors and will learn which sources to use to get more help online (official R documentation and forums).

Course setup

• Q1: Introduction to R and Rstudio
• Q2: Vectors and data types
• Q3: More vectors and matrices
• Q4: Data.frame
• Q5: Importing and saving data
• Q6: Basics of plotting data
• Q7: Editing plots
• Q8: Applied statistical techniques with R
• Q9: Getting help

The course is being offered online and runs for 3 weeks with a 1-day per week format. This makes the course less intensive and gives participants the opportunity to practise what they learn before progressing to the next chapter of the course."

General information

Fees ¹

¹ The course fee includes a reader, coffee/tea, and lunches. It does not include accommodation
² The Early-Bird Fee generally applies to anyone who REGISTERS AT LEAST 4 WEEKS PRIOR TO THE START OF THE COURSE

More information

Claudius van de Vijver (PE&RC)
Phone: +31 (0) 317 485116
Email: claudius.vandevijver@wur.nl

Lennart Suselbeek (PE&RC)
Phone: +31 (0) 317 485426
Email: lennart.suselbeek@wur.nl

Registration

At this moment, this course is not scheduled yet. However, if you register your interest in this activity below, we will inform you as soon as the course is scheduled and registration of participation is opened.