Introduction to R and R Studio (online) - December 2022

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Please note that, at this stage, this event is fully booked. Nevertheless, you are most welcome to register for this event, and accordingly, we will place you in a waiting list. Should any of the registered participants cancel his/her registration (which is quite common), we will notify you and ask you whether you would still like to participate in this event. If we do not contact you again with respect to this event, you may assume that no vacancies have arisen.

 

 

 

Introduction to R and R Studio (online) PE&RC logo klein transparant.png

Tuesday 6, Friday 9, Tuesday 13, Friday 16 December 2022

Scope

The aim of this course is to introduce the R programming language and how to use it to perform statistical inference and data visualization. Participants will be introduced to the R language syntax, basic types of data in R, how to explore data through descriptive statistics and visualization and how to apply a selection of basic techniques for statistical inference. The focus of the course is on the application of these techniques with R, and not on the underlying statistical theory which can be learnt in other courses. The course will be a combination of lectures, interactive live coding, individual exercises and self-study.

Learning Outcomes
  • Getting familiar with programming in a dynamic language in general and with R specifically
  • Introduce participants to the RStudio IDE (scripts, projects, customizing RStudio)
  • First, 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
  • This will be followed by a strong foundation on the basic types of data in R (vectors, matrices, lists, data frames) and how to work with them (access data, modify, filter). A good understanding on R data types facilitates further learning and understanding of R code
  • Next, participants will learn how to import and export data and will get to know the test datasets that R provides for practicing their skills. This will include understanding how to prepare data in a spreadsheet such that it can be imported efficiently into R
  • Participants will also learn how to visualize data using the basic R plotting tools and we will cover common statistical plots (scatter plots, bar plots, box plots, histograms), with an emphasis on exploratory data analysis (detecting outliers, visualize correlations and patterns) as well as visualizing results of statistical models. Participants will also learn how to customize the appearance of plots (labels, colors, legends, margins) so that they are publication ready
  • Finally, participants will be taught how to apply basic techniques of statistical inference from experimental data, including analysis of variance, linear models, t-test and testing the hypothesis behind these models.
Course setup

The course is spread across four days in two consecutive weeks and takes place on a dedicated Microsoft Teams group that will be created for the course. Each day of the course will be broken into three sections by a lunch break (1 hour) and two shorter breaks (20 minutes). Each section is chaired by one of the instructors who will share his computer screen with the rest of participants. During a section, theoretical concepts will be taught via a presentation, mixed with live coding practice, interaction with participants as well as short exercises (2 – 3 minutes each) performed by participants on their own. The other instructor will be answering questions on the chat of the Teams group.

Target Group The course is aimed at PhD candidates, postdocs, and academic staff
Group Size 24 participants
Course duration 4 days (6 hours per day) from 9:00 to 15:00 hours 
Language of instruction English
Frequency of recurrence Twice a year
Number of credits 0.9 ECTS
Lecturers Ioannis Baltzakis, Alejandro Morales
Prior knowledge No prior knowledge of R is expected from the participants
Estimated self-study/practice time 2 hours
Location Online (Microsoft Teams)

 

Fees 
  EARLY-BIRD FEE 1 REGULAR FEE 1
PE&RC / WIMEK / WASS / EPS / VLAG / WIAS PhD candidates with an approved TSP € 115,- € 165,-
PE&RC postdocs and staff  € 220,- € 270,-
All other academic participants € 270,- € 320,-
Non academic participants € 385,- € 435,-

1 The Early-Bird Fee applies to anyone who REGISTERS ON OR BEFORE 8 NOVEMBER 2022

Note:

  • If you need an invoice to complete your payment, please send an email to office.pe@wur.nl, including ALL relevant details that should be mentioned on the invoice (e.g., purchase order no., specific addresses, attendees, etc.).
  • Please make sure that your payment is arranged within two weeks after your registration.
  • It is the participant's responsibility to make sure that he/she (or his/her secretary) completes the payment correctly and in time.
PE&RC Cancellation Conditions
  • Up to 1 (one) week prior to the start of the course, cancellation is free of charge.
  • In case of cancellation within one week prior to the start of the course, a fee of € 270,- will be charged.
  • If you do not show at all, a fee of € 385,- will nevertheless be charged.
  • Furthermore, please be informed that if the software on your device is not working properly at the start of the course, you will NOT be able to participate. Please note that this will be at your own risk, fees will NOT be reimbursed. 

Note: If you would like to cancel your registration, ALWAYS inform us (and do note that you will be kept to the cancellation conditions)

More information

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

Registration

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